JMSLTM Numerical Library 6.1
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

A

abs(Complex) - Static method in class com.imsl.math.Complex
Returns the absolute value (modulus) of a Complex, |z|.
abs(int) - Static method in class com.imsl.math.JMath
Returns the absolute value of an int.
abs(long) - Static method in class com.imsl.math.JMath
Returns the absolute value of a long.
abs(float) - Static method in class com.imsl.math.JMath
Returns the absolute value of a float.
abs(double) - Static method in class com.imsl.math.JMath
Returns the absolute value of a double.
ABS_CORRELATION_COEFFICIENT - Static variable in class com.imsl.stat.Dissimilarities
Indicates the absolute value of the correlation coefficient distance method.
ABS_COSINE - Static variable in class com.imsl.stat.Dissimilarities
Indicates the absolute value of the cosine of the angle between the vectors distance method.
absolute(int) - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the given row number in this ResultSet object.
AbstractChartNode - Class in com.imsl.chart
The base class of all of the nodes in both the 2D and 3D chart trees.
AbstractChartNode(AbstractChartNode) - Constructor for class com.imsl.chart.AbstractChartNode
 
AbstractFlatFile - Class in com.imsl.io
Reads a text or binary file as a ResultSet.
AbstractFlatFile() - Constructor for class com.imsl.io.AbstractFlatFile
Initializes an AbstractFlatFile.
AbstractFlatFile.FlatFileSQLException - Exception in com.imsl.io
A SQLException thrown by the AbstractFlatFile class.
accrint(GregorianCalendar, GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the interest which has accrued on a security that pays interest periodically.
accrintm(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the interest which has accrued on a security that pays interest at maturity.
ACCUMULATE - Static variable in class com.imsl.math.NumericalDerivatives
Indicates the accumulation of the result from whatever type of differences have been specified previously into initial values of the Jacobian.
acos(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse cosine (arc cosine) of a Complex, with branch cuts outside the interval [-1,1] along the real axis.
acos(double) - Static method in class com.imsl.math.JMath
Returns the inverse (arc) cosine of a double.
acosh(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse hyperbolic cosine (arc cosh) of a Complex, with a branch cut at values less than one along the real axis.
acosh(double) - Static method in class com.imsl.math.Hyperbolic
Returns the inverse hyperbolic cosine of its argument.
Activation - Interface in com.imsl.datamining.neural
Interface implemented by perceptron activation functions.
add(Complex, Complex) - Static method in class com.imsl.math.Complex
Returns the sum of two Complex objects, x+y.
add(Complex, double) - Static method in class com.imsl.math.Complex
Returns the sum of a Complex and a double, x+y.
add(double, Complex) - Static method in class com.imsl.math.Complex
Returns the sum of a double and a Complex, x+y.
add(Complex[][], Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Add two rectangular Complex arrays, a + b.
add(Complex, Complex, ComplexSparseMatrix, ComplexSparseMatrix) - Static method in class com.imsl.math.ComplexSparseMatrix
Performs element-wise addition of two complex sparse matrices A, B of type ComplexSparseMatrix, C leftarrow alpha A + beta B.
add(double[][], double[][]) - Static method in class com.imsl.math.Matrix
Add two rectangular arrays, a + b.
add(Physical, Physical) - Static method in class com.imsl.math.Physical
Add two compatible Physical objects.
add(double, double, SparseMatrix, SparseMatrix) - Static method in class com.imsl.math.SparseMatrix
Performs element-wise addition of two real sparse matrices A, B of type SparseMatrix, C leftarrow alpha A + beta B.
addCenterLine() - Method in class com.imsl.chart.qc.ShewhartControlChart
Adds the center line to the control chart and returns the newly added line.
addControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart
Adds a control limit to the chart.
addCumulativeLine(AxisXY) - Method in class com.imsl.chart.qc.ParetoChart
Adds a cumulative line to the specified axis.
addCumulativeLine() - Method in class com.imsl.chart.qc.ParetoChart
Creates a new right-side axis and adds a cumulative line to it.
addDataMarkers() - Method in class com.imsl.chart.qc.CuSumStatus
Adds the original data to the chart on a newly created axis.
addDataMarkers(AxisXY) - Method in class com.imsl.chart.qc.CuSumStatus
Adds the original data to the chart.
ADDITIVE - Static variable in class com.imsl.stat.ARMAOutlierIdentification
Indicates detection of an additive outlier.
ADDITIVE - Static variable in class com.imsl.stat.AutoARIMA
Indicates detection of an additive outlier.
addLegendItem(int, ChartNode) - Method in class com.imsl.chart.Chart
Adds a legend to this ChartNode.
addLowerControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart
Creates lower ControlLimit, adds it to the control chart, and returns the newly created object.
addMouseListener(MouseListener) - Method in class com.imsl.chart.Chart
Adds a MouseListener to the component associated with this chart.
addMouseMotionListener(MouseMotionListener) - Method in class com.imsl.chart.Chart
Adds a MouseMotionListener to the component associated with this chart.
addNode(Node) - Method in class com.imsl.datamining.neural.Layer
Associates a Perceptron with this Layer.
addPickListener(PickListener) - Method in class com.imsl.chart.ChartNode
Adds a PickListener to this node.
addPostRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart
Adds a Paint object to draw to the canvas after the the 3D image is rendered.
addPreRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart
Adds a Paint object to draw to the canvas before the the 3D image is rendered.
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AmbientLight
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Axis3D
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisBox
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisLabel
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisLine
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisTitle
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisXYZ
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Background
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Chart3D
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ChartLights
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ChartNode3D
Called to add this object to the scene graph.
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ColormapLegend
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Data
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.DirectionalLight
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.MajorTick
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.PointLight
 
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Surface
 
addUpperControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart
Creates upper ControlLimit, adds it to the control chart, and returns the newly created object.
addWecoLimits() - Method in class com.imsl.chart.qc.ShewhartControlChart
Adds lines for the Western Electric Company Rules.
ADJUSTED_R_SQUARED_CRITERION - Static variable in class com.imsl.stat.SelectionRegression
Indicates R^2_a (adjusted R^2) criterion regression.
AFTER_SUCCESSFUL_STEP - Static variable in class com.imsl.math.ODE
Used by method examineStep to indicate examining after a successful step
AFTER_UNSUCCESSFUL_STEP - Static variable in class com.imsl.math.ODE
Used by method examineStep to indicate examining after an unsuccessful step
afterLast() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the end of this ResultSet object, just after the last row.
AIC - Static variable in class com.imsl.stat.AutoARIMA
Indicates that Akaike's information criterion (AIC) is used in the optimum model determination.
AICC - Static variable in class com.imsl.stat.AutoARIMA
Indicates that Akaike's corrected information criterion (AICC) is used in the optimum model determination.
ALL - Static variable in class com.imsl.stat.RegressorsForGLM
The n indicator variables are the dummy variables.
allConverged() - Method in class com.imsl.math.ZerosFunction
Returns true if the iterations for all of the roots have converged.
ALPHA_FACTOR_ANALYSIS - Static variable in class com.imsl.stat.FactorAnalysis
Indicates alpha factor analysis.
AmbientLight - Class in com.imsl.chart3d
An ambient light.
AmbientLight(Chart3D) - Constructor for class com.imsl.chart3d.AmbientLight
Creates an ambient light.
amordegrc(double, GregorianCalendar, GregorianCalendar, double, int, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the depreciation for each accounting period.
amorlinc(double, GregorianCalendar, GregorianCalendar, double, int, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the depreciation for each accounting period.
amultp(double[], double[]) - Method in interface com.imsl.math.ConjugateGradient.Function
A user-supplied function which computes z=Ap.
amultp(double[], double[]) - Method in interface com.imsl.math.GenMinRes.Function
Used to compute z = Ap where A is the matrix of coefficients to solve and p and z are arrays of length n, the order of matrix A.
ANCOVA - Class in com.imsl.stat
Analyzes a one-way classification model with covariates.
ANCOVA(double[][], double[][][]) - Constructor for class com.imsl.stat.ANCOVA
Constructs a one-way classification model with covariates.
ANGLE_IN_RADIANS - Static variable in class com.imsl.stat.Dissimilarities
Indicates the angle in radians (0, pi) between the lines through the origin defined by the vectors distance method.
Annotation - Class in com.imsl.chart
Draws an annotation.
Annotation(ChartNode, Text, double, double) - Constructor for class com.imsl.chart.Annotation
Creates a Text object at the specific x,y location in chart coordinates.
Annotation(ChartNode, String, double, double) - Constructor for class com.imsl.chart.Annotation
Draws a String at the specific x,y location in chart coordinates.
Annotation(ChartNode, Image, double, double) - Constructor for class com.imsl.chart.Annotation
Renders an Image object centered at an x,y location in chart coordinates.
ANNUAL - Static variable in class com.imsl.finance.Bond
Coupon payments are made annually.
ANOVA - Class in com.imsl.stat
Analysis of Variance table and related statistics.
ANOVA(double[][]) - Constructor for class com.imsl.stat.ANOVA
/** Analyzes a one-way classification model.
ANOVA(double, double, double, double, double) - Constructor for class com.imsl.stat.ANOVA
Construct an analysis of variance table and related statistics.
ANOVAFactorial - Class in com.imsl.stat
Analyzes a balanced factorial design with fixed effects.
ANOVAFactorial(int, int[], double[]) - Constructor for class com.imsl.stat.ANOVAFactorial
Constructor for ANOVAFactorial.
AR_1 - Static variable in class com.imsl.stat.ARMAEstimateMissing
Indicates that missing values should be estimated using an autoregressive time series with 1 lag.
AR_P - Static variable in class com.imsl.stat.ARMAEstimateMissing
Indicates that missing values should be estimated using an autoregressive time series with a maximum lag of maxLag.
ARAutoUnivariate - Class in com.imsl.stat
Automatically determines the best autoregressive time series model using Akaike's Information Criterion.
ARAutoUnivariate(int, double[]) - Constructor for class com.imsl.stat.ARAutoUnivariate
ARAutoUnivariate constructor.
ARAutoUnivariate.TriangularMatrixSingularException - Exception in com.imsl.stat
 
ARAutoUnivariate.TriangularMatrixSingularException(String) - Constructor for exception com.imsl.stat.ARAutoUnivariate.TriangularMatrixSingularException
 
ARAutoUnivariate.TriangularMatrixSingularException(String, Object[]) - Constructor for exception com.imsl.stat.ARAutoUnivariate.TriangularMatrixSingularException
 
argument(Complex) - Static method in class com.imsl.math.Complex
Returns the argument (phase) of a Complex, in radians, with a branch cut along the negative real axis.
ARMA - Class in com.imsl.stat
Computes least-square estimates of parameters for an ARMA model.
ARMA(int, int, double[]) - Constructor for class com.imsl.stat.ARMA
Constructor for ARMA.
ARMA.IllConditionedException - Exception in com.imsl.stat
The problem is ill-conditioned.
ARMA.IllConditionedException(String) - Constructor for exception com.imsl.stat.ARMA.IllConditionedException
Constructs an IllConditionedException with the specified detail message.
ARMA.IllConditionedException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.IllConditionedException
Constructs an IllConditionedException with the specified detail message.
ARMA.IncreaseErrRelException - Exception in com.imsl.stat
The bound for the relative error is too small.
ARMA.IncreaseErrRelException(String) - Constructor for exception com.imsl.stat.ARMA.IncreaseErrRelException
Constructs an IncreaseErrRelException with the specified detail message.
ARMA.IncreaseErrRelException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.IncreaseErrRelException
Constructs an IncreaseErrRelException with the specified detail message.
ARMA.MatrixSingularException - Exception in com.imsl.stat
The input matrix is singular.
ARMA.MatrixSingularException(String) - Constructor for exception com.imsl.stat.ARMA.MatrixSingularException
Constructs an MatrixSingularException with the specified detail message.
ARMA.MatrixSingularException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.MatrixSingularException
Constructs an MatrixSingularException with the specified detail message.
ARMA.NewInitialGuessException - Exception in com.imsl.stat
The iteration has not made good progress.
ARMA.NewInitialGuessException(String) - Constructor for exception com.imsl.stat.ARMA.NewInitialGuessException
Constructs an NewInitialGuessException with the specified detail message.
ARMA.NewInitialGuessException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.NewInitialGuessException
Constructs an NewInitialGuessException with the specified detail message.
ARMA.NoProgressException - Exception in com.imsl.stat
The algorithm is not making any progress, try new initial guess.
ARMA.NoProgressException() - Constructor for exception com.imsl.stat.ARMA.NoProgressException
 
ARMA.NoProgressException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.NoProgressException
 
ARMA.NoProgressException(Object[]) - Constructor for exception com.imsl.stat.ARMA.NoProgressException
 
ARMA.TooManyCallsException - Exception in com.imsl.stat
The number of calls to the function has exceeded the maximum number of iterations times the number of moving average (MA) parameters + 1.
ARMA.TooManyCallsException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyCallsException
Constructs an TooManyCallsException with the specified detail message.
ARMA.TooManyCallsException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyCallsException
Constructs an TooManyCallsException with the specified detail message.
ARMA.TooManyFcnEvalException - Exception in com.imsl.stat
Maximum number of function evaluations exceeded.
ARMA.TooManyFcnEvalException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyFcnEvalException
Constructs an TooManyFcnEvalException with the specified detail message.
ARMA.TooManyFcnEvalException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyFcnEvalException
Constructs an TooManyFcnEvalException with the specified detail message.
ARMA.TooManyITNException - Exception in com.imsl.stat
Maximum number of iterations exceeded.
ARMA.TooManyITNException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyITNException
Constructs an TooManyITNException with the specified detail message.
ARMA.TooManyITNException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyITNException
 
ARMA.TooManyJacobianEvalException - Exception in com.imsl.stat
Maximum number of Jacobian evaluations exceeded.
ARMA.TooManyJacobianEvalException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyJacobianEvalException
Constructs an TooManyJacobianEvalException with the specified detail message.
ARMA.TooManyJacobianEvalException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyJacobianEvalException
Constructs an TooManyJacobianEvalException with the specified detail message.
ARMAEstimateMissing - Class in com.imsl.stat
Estimates missing values in a time series collected with equal spacing.
ARMAEstimateMissing(int[], double[]) - Constructor for class com.imsl.stat.ARMAEstimateMissing
Constructor for ARMAEstimateMissing.
ARMAMaxLikelihood - Class in com.imsl.stat
Computes maximum likelihood estimates of parameters for an ARMA model with p and q autoregressive and moving average terms respectively.
ARMAMaxLikelihood(int, int, double[]) - Constructor for class com.imsl.stat.ARMAMaxLikelihood
Constructor for ARMAMaxLikelihood.
ARMAMaxLikelihood.InitialMAException - Exception in com.imsl.stat
The initial values for the moving average parameters are not invertible.
ARMAMaxLikelihood.InitialMAException(String) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.InitialMAException
Constructs an InitialMAException with the specified detail message.
ARMAMaxLikelihood.InitialMAException(String, Object[]) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.InitialMAException
Constructs an InitialMAException with the specified detail message.
ARMAMaxLikelihood.NonInvertibleException - Exception in com.imsl.stat
The solution is noninvertible.
ARMAMaxLikelihood.NonInvertibleException(String) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonInvertibleException
Constructs a NonInvertible exception with the specified detail message.
ARMAMaxLikelihood.NonInvertibleException(String, Object[]) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonInvertibleException
Constructs a NonInvertibleException exception with the specified detail message.
ARMAMaxLikelihood.NonStationaryException - Exception in com.imsl.stat
The solution is nonstationary.
ARMAMaxLikelihood.NonStationaryException(String) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonStationaryException
Constructs a NonStationary exception with the specified detail message.
ARMAMaxLikelihood.NonStationaryException(String, Object[]) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonStationaryException
Constructs a NonStationary exception with the specified detail message.
ARMAOutlierIdentification - Class in com.imsl.stat
Detects and determines outliers and simultaneously estimates the model parameters in a time series whose underlying outlier free series follows a general seasonal or nonseasonal ARMA model.
ARMAOutlierIdentification(double[]) - Constructor for class com.imsl.stat.ARMAOutlierIdentification
Constructor for ARMAOutlierIdentification.
ARSeasonalFit - Class in com.imsl.stat
Estimates the optimum seasonality parameters for a time series using an autoregressive model, AR(p), to represent the time series.
ARSeasonalFit(int, int[][], double[]) - Constructor for class com.imsl.stat.ARSeasonalFit
Constructor for ARSeasonalFit.
ascending(int[]) - Static method in class com.imsl.stat.Sort
Function to sort an integer array into ascending order.
ascending(int[], int[]) - Static method in class com.imsl.stat.Sort
Sort an integer array into ascending order and returns the permutation vector.
ascending(double[]) - Static method in class com.imsl.stat.Sort
Sort an array into ascending order.
ascending(double[], int[]) - Static method in class com.imsl.stat.Sort
Sort an array into ascending order and returns the permutation vector.
ascending(double[][], int) - Static method in class com.imsl.stat.Sort
Sort a matrix into ascending order by the first nkeys.
ascending(double[][], int[]) - Static method in class com.imsl.stat.Sort
Sort a matrix into ascending order by specified keys.
ascending(double[][], int, int[]) - Static method in class com.imsl.stat.Sort
Sort an array into ascending order by the first nkeys and returns the permutation vector.
ascending(double[][], int[], int[]) - Static method in class com.imsl.stat.Sort
Sort a matrix into ascending order by specified keys and returns the permutation vector.
asin(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse sine (arc sine) of a Complex, with branch cuts outside the interval [-1,1] along the real axis.
asin(double) - Static method in class com.imsl.math.JMath
Returns the inverse (arc) sine of a double.
asinh(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse hyperbolic sine (arc sinh) of a Complex, with branch cuts outside the interval [-i,i].
asinh(double) - Static method in class com.imsl.math.Hyperbolic
Returns the inverse hyperbolic sine of its argument.
AT_BEGINNING_OF_PERIOD - Static variable in class com.imsl.finance.Finance
Flag used to indicate that payment is made at the beginning of each period.
AT_END_OF_PERIOD - Static variable in class com.imsl.finance.Finance
Flag used to indicate that payment is made at the end of each period.
atan(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse tangent (arc tangent) of a Complex, with branch cuts outside the interval [-i,i] along the imaginary axis.
atan(double) - Static method in class com.imsl.math.JMath
Returns the inverse (arc) tangent of a double.
atan2(double, double) - Static method in class com.imsl.math.JMath
Returns the angle corresponding to a Cartesian point.
atanh(Complex) - Static method in class com.imsl.math.Complex
Returns the inverse hyperbolic tangent (arc tanh) of a Complex, with branch cuts outside the interval [-1,1] on the real axis.
atanh(double) - Static method in class com.imsl.math.Hyperbolic
Returns the inverse hyperbolic tangent of its argument.
AutoARIMA - Class in com.imsl.stat
Automatically identifies time series outliers, determines parameters of a multiplicative seasonal text{ARIMA}(p,0,q)times(0,d,0)_s model and produces forecasts that incorporate the effects of outliers whose effects persist beyond the end of the series.
AutoARIMA(int[], double[]) - Constructor for class com.imsl.stat.AutoARIMA
Constructor for AutoARIMA.
AutoARIMA.NoAcceptableModelFoundException - Exception in com.imsl.stat
No appropriate ARIMA model could be found.
AutoARIMA.NoAcceptableModelFoundException(String) - Constructor for exception com.imsl.stat.AutoARIMA.NoAcceptableModelFoundException
Constructs a NoAcceptableModelFoundException exception with the specified detail message.
AutoARIMA.NoAcceptableModelFoundException(String, Object[]) - Constructor for exception com.imsl.stat.AutoARIMA.NoAcceptableModelFoundException
Constructs a NoAcceptableModelFoundException exception with the specified detail message.
AutoCorrelation - Class in com.imsl.stat
Computes the sample autocorrelation function of a stationary time series.
AutoCorrelation(double[], int) - Constructor for class com.imsl.stat.AutoCorrelation
Constructor to compute the sample autocorrelation function of a stationary time series.
AutoCorrelation.NonPosVariancesException - Exception in com.imsl.stat
The problem is ill-conditioned.
AutoCorrelation.NonPosVariancesException(String) - Constructor for exception com.imsl.stat.AutoCorrelation.NonPosVariancesException
Constructs an NonPosVariancesException with the specified detail message.
AutoCorrelation.NonPosVariancesException(String, Object[]) - Constructor for exception com.imsl.stat.AutoCorrelation.NonPosVariancesException
Constructs an NonPosVariancesException with the specified detail message.
AUTOMATIC - Static variable in class com.imsl.chart.Treemap
Flag to set the treemap orientation automatically.
AUTOSCALE_DATA - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that autoscaling is to be done by scanning the data nodes.
AUTOSCALE_DENSITY - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that autoscaling is to adjust the "Density" attribute.
AUTOSCALE_NUMBER - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that autoscaling is to adjust the "Number" attribute.
AUTOSCALE_OFF - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that autoscaling is turned off.
AUTOSCALE_WINDOW - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that autoscaling is to be done by using the "Window" attribute.
Axis - Class in com.imsl.chart
The Axis node provides the mapping for all of its children from the user coordinate space to the device (screen) space.
Axis(Chart) - Constructor for class com.imsl.chart.Axis
Contructs an Axis node.
Axis1D - Class in com.imsl.chart
An x-axis or a y-axis.
Axis3D - Class in com.imsl.chart3d
An x-axis, y-axis or a z-axis.
AXIS_TITLE_AT_END - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "AxisTitlePosition" indicating that the axis title should be placed at the end of the axis.
AXIS_TITLE_PARALLEL - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "AxisTitlePosition" indicating that the axis title should be placed parallel to the axis.
AXIS_X - Static variable in class com.imsl.chart.AbstractChartNode
Flag to indicate x-axis.
AXIS_X_TOP - Static variable in class com.imsl.chart.ChartNode
Flag to indicate x-axis placed on top of the chart.
AXIS_Y - Static variable in class com.imsl.chart.AbstractChartNode
Flag to indicate y-axis.
AXIS_Y_RIGHT - Static variable in class com.imsl.chart.ChartNode
Flag to indicate y-axis placed to the right of the chart.
AXIS_Z - Static variable in class com.imsl.chart.AbstractChartNode
Flag to indicate z-axis.
AxisBox - Class in com.imsl.chart3d
Box behind the axis.
AxisLabel - Class in com.imsl.chart
The labels on an axis.
AxisLabel - Class in com.imsl.chart3d
The labels on an axis.
AxisLine - Class in com.imsl.chart
The axis line.
AxisLine - Class in com.imsl.chart3d
The axis line.
AxisR - Class in com.imsl.chart
The R-axis in a polar plot.
AxisRLabel - Class in com.imsl.chart
The labels on an axis.
AxisRLine - Class in com.imsl.chart
The radius axis line in a polar plot.
AxisRMajorTick - Class in com.imsl.chart
The major tick marks for the radius axis in a polar plot.
AxisTheta - Class in com.imsl.chart
The angular axis in a polar plot.
AxisTitle - Class in com.imsl.chart
The title on an axis.
AxisTitle - Class in com.imsl.chart3d
Axis title.
AxisUnit - Class in com.imsl.chart
The unit title on an axis.
AxisXY - Class in com.imsl.chart
The axes for an x-y chart.
AxisXY(Chart) - Constructor for class com.imsl.chart.AxisXY
Create an AxisXY.
AxisXYZ - Class in com.imsl.chart3d
The axes for an x-y-z chart.
AxisXYZ(Chart3D) - Constructor for class com.imsl.chart3d.AxisXYZ
Create an AxisXYZ.

B

Background - Class in com.imsl.chart
The background of a chart.
Background - Class in com.imsl.chart3d
Background of the chart.
backward(Complex[]) - Method in class com.imsl.math.ComplexFFT
Compute the complex periodic sequence from its Fourier coefficients.
backward(double[]) - Method in class com.imsl.math.FFT
Compute the real periodic sequence from its Fourier coefficients.
BACKWARD_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression
Indicates backward regression.
Bar - Class in com.imsl.chart
A bar chart.
Bar(AxisXY) - Constructor for class com.imsl.chart.Bar
Constructs a bar chart.
Bar(AxisXY, double[]) - Constructor for class com.imsl.chart.Bar
Constructs a simple bar chart using supplied y data.
Bar(AxisXY, double[], double[]) - Constructor for class com.imsl.chart.Bar
Constructs a simple bar chart using supplied x and y data.
Bar(AxisXY, double[][]) - Constructor for class com.imsl.chart.Bar
Constructs a grouped bar chart using supplied x and y data.
Bar(AxisXY, double[], double[][]) - Constructor for class com.imsl.chart.Bar
Constructs a grouped bar chart using supplied x and y data.
Bar(AxisXY, double[][][]) - Constructor for class com.imsl.chart.Bar
Constructs a stacked, grouped bar chart using supplied y data.
Bar(AxisXY, double[], double[][][]) - Constructor for class com.imsl.chart.Bar
Constructs a stacked, grouped bar chart using supplied x and y data.
BAR_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.ChartNode
Flag to indicate a horizontal bar chart.
BAR_TYPE_VERTICAL - Static variable in class com.imsl.chart.ChartNode
Flag to indicate a vertical bar chart.
BarItem - Class in com.imsl.chart
A single bar in a bar chart.
BarSet - Class in com.imsl.chart
A set of bars in a bar chart.
BARTLETTS_FORMULA - Static variable in class com.imsl.stat.AutoCorrelation
Indicates standard error computation using Bartlett's formula.
BARTLETTS_FORMULA - Static variable in class com.imsl.stat.CrossCorrelation
Indicates standard error computation using Bartlett's formula.
BARTLETTS_FORMULA_NOCC - Static variable in class com.imsl.stat.CrossCorrelation
Indicates standard error computation using Bartlett's formula with the assumption of no cross-correlation.
basis(int, double) - Method in interface com.imsl.stat.RegressionBasis
Public interface for the nonlinear least-squares function.
Basis30e360 - Static variable in class com.imsl.finance.DayCountBasis
Computations based on the assumption of 30 days per month and 360 days per year.
BasisActual360 - Static variable in class com.imsl.finance.DayCountBasis
Computations are based on the number of days in a month based on the actual calendar value and the number of days, but assuming 360 days per year.
BasisActual365 - Static variable in class com.imsl.finance.DayCountBasis
Computations are based on the number of days in a month based on the actual calendar value and the number of days, but assuming 365 days per year.
BasisActualActual - Static variable in class com.imsl.finance.DayCountBasis
Computations are based on the actual calendar.
BasisNASD - Static variable in class com.imsl.finance.DayCountBasis
Computations based on the assumption of 30 days per month and 360 days per year.
BasisPart - Interface in com.imsl.finance
Component of DayCountBasis.
BasisPart30E360 - Static variable in class com.imsl.finance.DayCountBasis
Computations based on the assumption of 30 days per month and 360 days per year.
BasisPart365 - Static variable in class com.imsl.finance.DayCountBasis
Computations based on the assumption of 365 days per year.
BasisPartActual - Static variable in class com.imsl.finance.DayCountBasis
Computations are based on the actual calendar.
BasisPartNASD - Static variable in class com.imsl.finance.DayCountBasis
Computations based on the assumption of 30 days per month and 360 days per year.
BEFORE_STEP - Static variable in class com.imsl.math.ODE
Used by method examineStep to indicate examining before the next step
beforeFirst() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the front of this ResultSet object, just before the first row.
BEGIN_COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a column label is to be returned.
BEGIN_COLUMN_LABELS - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for beginning a column label row is to be returned.
BEGIN_ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatted string for beginning an entry is to be returned.
BEGIN_MATRIX - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for beginning a matrix is to be returned.
BEGIN_ROW - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for beginning a row is to be returned.
BEGIN_ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for beginning a row label is to be returned.
beginGet() - Method in class com.imsl.io.AbstractFlatFile
This method should be called at the start of every getType method.
Bessel - Class in com.imsl.math
Collection of Bessel functions.
beta(double, double) - Static method in class com.imsl.math.Sfun
Returns the value of the beta function.
beta(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the beta cumulative probability distribution function.
beta(double, double, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the beta cumulative probability distribution function.
beta(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the beta probability density function.
betaIncomplete(double, double, double) - Static method in class com.imsl.math.Sfun
Returns the incomplete beta function ratio.
betaMean(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the mean of the beta cumulative probability distribution function
betaVariance(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the variance of the beta cumulative probability distribution function
BIC - Static variable in class com.imsl.stat.AutoARIMA
Indicates that the Bayesian information criterion (BIC) is used in the optimum model determination.
BIMONTHLY - Static variable in class com.imsl.finance.Bond
Coupon payments are made bimonthly (6 times per year).
BINARY_VARIABLE - Static variable in class com.imsl.io.MPSReader
Variable must be either 0 or 1.
BinaryClassification - Class in com.imsl.datamining.neural
Classifies patterns into two classes.
BinaryClassification(Network) - Constructor for class com.imsl.datamining.neural.BinaryClassification
Creates a binary classifier.
binomial(int, int, double) - Static method in class com.imsl.stat.Cdf
Evaluates the binomial cumulative probability distribution function.
binomial(int, int, double) - Static method in class com.imsl.stat.Pdf
Evaluates the binomial probability density function.
bivariateNormal(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the bivariate normal cumulative probability distribution function.
BLUE - Static variable in interface com.imsl.chart.Colormap
Linear blue colormap.
BLUE_GREEN_RED_YELLOW - Static variable in interface com.imsl.chart.Colormap
Blue/green/red/yellow colormap.
BLUE_RED - Static variable in interface com.imsl.chart.Colormap
Blue/red colormap.
BLUE_WHITE - Static variable in interface com.imsl.chart.Colormap
Blue/white colormap.
Bond - Class in com.imsl.finance
Collection of bond functions.
Bond() - Constructor for class com.imsl.finance.Bond
 
BONFERRONI - Static variable in class com.imsl.stat.ANOVA
The Bonferroni method
BOUNDED_SCALING - Static variable in class com.imsl.datamining.neural.ScaleFilter
Flag to indicate bounded scaling.
BOUNDED_Z_SCORE_SCALING_MEAN_STDEV - Static variable in class com.imsl.datamining.neural.ScaleFilter
Flag to indicate bounded z-score scaling using the mean and standard deviation.
BOUNDED_Z_SCORE_SCALING_MEDIAN_MAD - Static variable in class com.imsl.datamining.neural.ScaleFilter
Flag to indicate bounded z-score scaling using the median and mean absolute difference.
BoundedLeastSquares - Class in com.imsl.math
Solves a nonlinear least-squares problem subject to bounds on the variables using a modified Levenberg-Marquardt algorithm.
BoundedLeastSquares(BoundedLeastSquares.Function, int, int, int, double[], double[]) - Constructor for class com.imsl.math.BoundedLeastSquares
Constructor for BoundedLeastSquares.
BoundedLeastSquares.FalseConvergenceException - Exception in com.imsl.math
False convergence - The iterates appear to be converging to a noncritical point.
BoundedLeastSquares.FalseConvergenceException(String) - Constructor for exception com.imsl.math.BoundedLeastSquares.FalseConvergenceException
Constructs an FalseConvergenceException with the specified detail message.
BoundedLeastSquares.FalseConvergenceException(String, Object[]) - Constructor for exception com.imsl.math.BoundedLeastSquares.FalseConvergenceException
Constructs an FalseConvergenceException with the specified detail message.
BoundedLeastSquares.Function - Interface in com.imsl.math
Public interface for the user-supplied function to evaluate the function that defines the least-squares problem.
BoundedLeastSquares.Jacobian - Interface in com.imsl.math
Public interface for the user-supplied function to compute the Jacobian.
BoundedLeastSquares.NoProgressException - Exception in com.imsl.math
The algorithm is not making any progress, try new initial guess.
BoundedLeastSquares.NoProgressException() - Constructor for exception com.imsl.math.BoundedLeastSquares.NoProgressException
 
BoundedLeastSquares.NoProgressException(String, Object[]) - Constructor for exception com.imsl.math.BoundedLeastSquares.NoProgressException
 
BoundedLeastSquares.NoProgressException(Object[]) - Constructor for exception com.imsl.math.BoundedLeastSquares.NoProgressException
 
BoundedVariableLeastSquares - Class in com.imsl.math
Solve a linear least-squares problem with bounds on the variables.
BoundedVariableLeastSquares(double[][], double[], double[], double[]) - Constructor for class com.imsl.math.BoundedVariableLeastSquares
Construct a new BoundedVariableLeastSquares instance to solve Ax-b subject to bounds on the variables.
BoundedVariableLeastSquares.TooManyIterException - Exception in com.imsl.math
Maximum number of iterations exceeded.
BoundedVariableLeastSquares.TooManyIterException(String) - Constructor for exception com.imsl.math.BoundedVariableLeastSquares.TooManyIterException
The maximum number of iterations has exceeded.
BoundedVariableLeastSquares.TooManyIterException(String, Object[]) - Constructor for exception com.imsl.math.BoundedVariableLeastSquares.TooManyIterException
The maximum number of iterations has exceeded.
BoxPlot - Class in com.imsl.chart
Draws a multiple-group Box plot.
BoxPlot(AxisXY, double[], double[][]) - Constructor for class com.imsl.chart.BoxPlot
Constructs a box plot chart node with specified x values.
BoxPlot(AxisXY, double[], BoxPlot.Statistics[]) - Constructor for class com.imsl.chart.BoxPlot
Constructs a box plot chart node with specified x values.
BoxPlot(AxisXY, double[][]) - Constructor for class com.imsl.chart.BoxPlot
Constructs a box plot chart.
BoxPlot.Statistics - Class in com.imsl.chart
Computes the statistics for one set of observations in a Boxplot.
BoxPlot.Statistics(double[]) - Constructor for class com.imsl.chart.BoxPlot.Statistics
Creates a new instance of BoxPlot.Statistics.
BOXPLOT_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.BoxPlot
Value for attribute "BoxPlotType" indicating that this is a horizontal box plot.
BOXPLOT_TYPE_VERTICAL - Static variable in class com.imsl.chart.BoxPlot
Value for attribute "BoxPlotType" indicating that this is a horizontal box plot.
breakPoint - Variable in class com.imsl.math.Spline
The breakpoint array of length n, where n is the number of piecewise polynomials.
BRESLOWS_APPROXIMATE - Static variable in class com.imsl.stat.ProportionalHazards
Breslows approximate method of handling ties.
BsInterpolate - Class in com.imsl.math
Extension of the BSpline class to interpolate data points.
BsInterpolate(double[], double[]) - Constructor for class com.imsl.math.BsInterpolate
Constructs a B-spline that interpolates the given data points.
BsInterpolate(double[], double[], int) - Constructor for class com.imsl.math.BsInterpolate
Constructs a B-spline that interpolates the given data points and order, using a default "not-a-knot" spline knot sequence.
BsInterpolate(double[], double[], int, double[]) - Constructor for class com.imsl.math.BsInterpolate
Constructs a B-spline that interpolates the given data points, using the specified order and knots.
BsLeastSquares - Class in com.imsl.math
Extension of the BSpline class to compute a least squares spline approximation to data points.
BsLeastSquares(double[], double[], int) - Constructor for class com.imsl.math.BsLeastSquares
Constructs a least squares B-spline approximation to the given data points.
BsLeastSquares(double[], double[], int, int) - Constructor for class com.imsl.math.BsLeastSquares
Constructs a least squares B-spline approximation to the given data points.
BsLeastSquares(double[], double[], int, int, double[], double[]) - Constructor for class com.imsl.math.BsLeastSquares
Constructs a least squares B-spline approximation to the given data points.
BSpline - Class in com.imsl.math
BSpline represents and evaluates univariate B-splines.
BSpline() - Constructor for class com.imsl.math.BSpline
 
BufferedPaint - Class in com.imsl.chart3d
A Paint object cached into an image.
BufferedPaint(Canvas3DChart.Paint, int, int, int, int, Component) - Constructor for class com.imsl.chart3d.BufferedPaint
The paint method in Canvas3DChart.Paint is written into an image of size width by height.
BW_LINEAR - Static variable in interface com.imsl.chart.Colormap
Black and white (grayscale) colormap.
byteValue() - Method in class com.imsl.math.Complex
Returns the value of the real part as a byte.

C

cancelRowUpdates() - Method in class com.imsl.io.AbstractFlatFile
Cancels the updates made to the current row in this ResultSet object.
Candlestick - Class in com.imsl.chart
Candlestick plot of stock data.
Candlestick(AxisXY, Date, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.Candlestick
Constructs a candlestick chart node beginning with specified start date.
Candlestick(AxisXY, double[], double[], double[], double[], double[]) - Constructor for class com.imsl.chart.Candlestick
Constructs a candlestick chart node at specified axis points.
CandlestickItem - Class in com.imsl.chart
A candlestick for the up days or the down days.
canonicalCorrelation(double[][]) - Method in class com.imsl.stat.Random
Method canonicalCorrelation generates a canonical correlation matrix from an arbitrarily distributed multivariate deviate sequence with nvar deviate variables, nseq steps in the sequence, and a Gaussian Copula dependence structure.
Canvas3DChart - Class in com.imsl.chart3d
A canvas for rendering a 3D chart.
Canvas3DChart() - Constructor for class com.imsl.chart3d.Canvas3DChart
Creates a Canvas3DChart with a new Chart3D object.
Canvas3DChart(Chart3D) - Constructor for class com.imsl.chart3d.Canvas3DChart
Creates a Canvas3DChart with a given Chart3D object.
Canvas3DChart.Paint - Interface in com.imsl.chart3d
Interface for 2D drawing on the canvas before or after the the 3D image is drawn.
capabilityIndexCp(double, double) - Method in class com.imsl.chart.qc.XbarR
Returns the capability index c_p

c_p=frac{mathrm{USL}-mathrm{LSL}}{6sigma}

capabilityIndexCp(double, double) - Method in class com.imsl.chart.qc.XbarS
Returns the capability index c_p

c_p=frac{mathrm{USL}-mathrm{LSL}}{6sigma}

capabilityIndexCpk(double, double) - Method in class com.imsl.chart.qc.XbarR
Returns the capability index c_{pk}

c_{pk}=minleft[frac{mathrm{USL}-bar{x}}{3sigma},frac{bar{x}-mathrm{LSL}}{3sigma}right]

capabilityIndexCpk(double, double) - Method in class com.imsl.chart.qc.XbarS
Returns the capability index c_{pk}

c_{pk}=minleft[frac{mathrm{USL}-bar{x}}{3sigma},frac{bar{x}-mathrm{LSL}}{3sigma}right]

CategoricalGenLinModel - Class in com.imsl.stat
Analyzes categorical data using logistic, probit, Poisson, and other linear models.
CategoricalGenLinModel(double[][], int) - Constructor for class com.imsl.stat.CategoricalGenLinModel
Constructs a new CategoricalGenLinModel.
CategoricalGenLinModel.ClassificationVariableException - Exception in com.imsl.stat
The ClassificationVariable vector has not been initialized.
CategoricalGenLinModel.ClassificationVariableException() - Constructor for exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableException
Constructs a ClassificationVariableException.
CategoricalGenLinModel.ClassificationVariableLimitException - Exception in com.imsl.stat
The Classification Variable limit set by the user through setUpperBound has been exceeded.
CategoricalGenLinModel.ClassificationVariableLimitException(int) - Constructor for exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableLimitException
Constructs a ClassificationVariableLimitException.
CategoricalGenLinModel.ClassificationVariableValueException - Exception in com.imsl.stat
The number of distinct values for each Classification Variable must be greater than 1.
CategoricalGenLinModel.ClassificationVariableValueException(int, int) - Constructor for exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableValueException
Constructs a ClassificationVariableValueException.
CategoricalGenLinModel.DeleteObservationsException - Exception in com.imsl.stat
The number of observations to be deleted (set by setObservationMax) has grown too large.
CategoricalGenLinModel.DeleteObservationsException(int) - Constructor for exception com.imsl.stat.CategoricalGenLinModel.DeleteObservationsException
Constructs a DeleteObservationsException.
CategoricalGenLinModel.RankDeficientException - Exception in com.imsl.stat
The model has been determined to be rank deficient.
CategoricalGenLinModel.RankDeficientException(int) - Constructor for exception com.imsl.stat.CategoricalGenLinModel.RankDeficientException
Constructs a RankDeficientException.
CChart - Class in com.imsl.chart.qc
CChart is a c-chart for monitoring the count of the number of defects when defects are rare.
CChart(AxisXY, int[]) - Constructor for class com.imsl.chart.qc.CChart
Creates a C-chart given the number of defects in a series of samples.
Cdf - Class in com.imsl.stat
Cumulative probability distribution functions.
cdf(double) - Method in interface com.imsl.stat.CdfFunction
Public interface for the user-supplied cumulative distribution function to be used by InverseCdf.
CdfFunction - Interface in com.imsl.stat
Public interface for the user-supplied cumulative distribution function to be used by InverseCdf and ChiSquaredTest.
ceil(double) - Static method in class com.imsl.math.JMath
Returns the value of a double rounded toward positive infinity to an integral value.
CENTER_MEAN - Static variable in class com.imsl.stat.ARSeasonalFit
Indicates the transformed series should be centered using the average of the differenced series.
CENTER_MEDIAN - Static variable in class com.imsl.stat.ARSeasonalFit
Indicates the transformed series should be centered using the median of the differenced series.
CENTRAL - Static variable in class com.imsl.math.NumericalDerivatives
Indicates central differences.
Chart - Class in com.imsl.chart
The root node of the chart tree.
Chart() - Constructor for class com.imsl.chart.Chart
This is the root of our tree, it has no parent.
Chart(Component) - Constructor for class com.imsl.chart.Chart
This is the root of our tree, it has no parent.
Chart(Image) - Constructor for class com.imsl.chart.Chart
This is the root of our tree, it has no parent.
chart - Variable in class com.imsl.chart.JPanelChart
The embedded chart.
Chart3D - Class in com.imsl.chart3d
Root node of a 3d chart tree.
Chart3D() - Constructor for class com.imsl.chart3d.Chart3D
Creates a new instance of Chart3D
ChartFunction - Interface in com.imsl.chart
An interface that allows a function to be plotted.
ChartLights - Class in com.imsl.chart3d
Default set of lights.
ChartNode - Class in com.imsl.chart
The base class of all of the nodes in the 2D chart tree.
ChartNode(ChartNode) - Constructor for class com.imsl.chart.ChartNode
Construct a ChartNode object.
ChartNode3D - Class in com.imsl.chart3d
The base class of all of the nodes in the 3D chart tree.
ChartNode3D(ChartNode3D) - Constructor for class com.imsl.chart3d.ChartNode3D
Construct a ChartNode3D object.
ChartServlet - Class in com.imsl.chart
The base class for chart servlets.
ChartServlet() - Constructor for class com.imsl.chart.ChartServlet
 
ChartSpline - Class in com.imsl.chart
Wrap a spline into a ChartFunction to be plotted.
ChartSpline(Spline) - Constructor for class com.imsl.chart.ChartSpline
Creates a ChartSpline from a Spline.
ChartSpline(Spline, int) - Constructor for class com.imsl.chart.ChartSpline
Creates a ChartSpline from the derivative of a Spline.
ChartTitle - Class in com.imsl.chart
The main title of a chart.
ChartXML - Class in com.imsl.chart.xml
Create a Chart from an XML file.
ChartXML(String) - Constructor for class com.imsl.chart.xml.ChartXML
Creates a ChartXML from an XML file.
ChartXML(String, boolean) - Constructor for class com.imsl.chart.xml.ChartXML
Creates a ChartXML from an XML file.
ChartXML(InputSource, boolean) - Constructor for class com.imsl.chart.xml.ChartXML
Creates a ChartXML from an XML source.
ChartXML(Document) - Constructor for class com.imsl.chart.xml.ChartXML
Creates a ChartXML from a DOM tree.
check(int) - Method in class com.imsl.chart.Draw
 
checkCompatibility(Physical, Physical) - Static method in class com.imsl.math.Physical
Checks the compatibility of two Physical objects.
checkerboard(int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a checkerboard pattern.
checkMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Check that all of the rows in the Complex matrix have the same length.
checkMatrix(double[][]) - Static method in class com.imsl.math.Matrix
Check that all of the rows in the matrix have the same length.
checkSquareMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Check that the Complex matrix is square.
checkSquareMatrix() - Method in class com.imsl.math.ComplexSparseMatrix
Check that the matrix is square.
checkSquareMatrix(double[][]) - Static method in class com.imsl.math.Matrix
Check that the matrix is square.
checkSquareMatrix() - Method in class com.imsl.math.SparseMatrix
Check that the matrix is square.
chi(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the chi-squared cumulative distribution function.
chi(double, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the chi-squared cumulative probability distribution function.
chi(double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the chi-squared probability density function
chiMean(double) - Static method in class com.imsl.stat.Cdf
Evaluates the mean of the chi-squared cumulative probability distribution function
ChiSquaredTest - Class in com.imsl.stat
Chi-squared goodness-of-fit test.
ChiSquaredTest(CdfFunction, double[], int) - Constructor for class com.imsl.stat.ChiSquaredTest
Constructor for the Chi-squared goodness-of-fit test.
ChiSquaredTest(CdfFunction, int, int) - Constructor for class com.imsl.stat.ChiSquaredTest
Constructor for the Chi-squared goodness-of-fit test
ChiSquaredTest(int) - Method in class com.imsl.stat.NormalityTest
Performs the chi-squared goodness-of-fit test.
ChiSquaredTest.DidNotConvergeException - Exception in com.imsl.stat
The iteration did not converge
ChiSquaredTest.DidNotConvergeException(String) - Constructor for exception com.imsl.stat.ChiSquaredTest.DidNotConvergeException
 
ChiSquaredTest.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.stat.ChiSquaredTest.DidNotConvergeException
 
ChiSquaredTest.NoObservationsException - Exception in com.imsl.stat
There are no observations.
ChiSquaredTest.NoObservationsException(String, Object[]) - Constructor for exception com.imsl.stat.ChiSquaredTest.NoObservationsException
 
ChiSquaredTest.NotCDFException - Exception in com.imsl.stat
The function is not a Cumulative Distribution Function (CDF).
ChiSquaredTest.NotCDFException(String, Object[]) - Constructor for exception com.imsl.stat.ChiSquaredTest.NotCDFException
 
chiVariance(double) - Static method in class com.imsl.stat.Cdf
Evaluates the variance of the chi-squared cumulative probability distribution function
Cholesky - Class in com.imsl.math
Cholesky factorization of a matrix of type double.
Cholesky(double[][]) - Constructor for class com.imsl.math.Cholesky
Create the Cholesky factorization of a symmetric positive definite matrix of type double.
Cholesky.NotSPDException - Exception in com.imsl.math
The matrix is not symmetric, positive definite.
Cholesky.NotSPDException() - Constructor for exception com.imsl.math.Cholesky.NotSPDException
 
circle(int, int, int) - Method in class com.imsl.chart.DrawMap
Sets a circle as the target.
classError(double[], int[], int) - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns the classification probability error for the input pattern and known target classification.
classify(double[][]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations using the linear or quadratic discriminant functions generated during the training process.
classify(double[][], int[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations using the linear or quadratic discriminant functions generated during the training process.
classify(double[][], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations and associated frequencies and weights using the linear or quadratic discriminant functions generated during the training process.
classify(double[][], int[], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations and associated frequencies and weights using the linear or quadratic discriminant functions generated during the training process.
classify(double[][], int[], int[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations and compare against known groups using the linear or quadratic discriminant functions generated during the training process.
classify(double[][], int[], int[], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Classify a set of observations, associated frequencies and weights, and compare against known groups using the linear or quadratic discriminant functions generated during the training process.
cleanup() - Method in class com.imsl.chart3d.Chart3D
Cleanup memory use and references used by the chart.
clearWarnings() - Method in class com.imsl.io.AbstractFlatFile
Clears all warnings reported on this ResultSet object.
clone(Map) - Method in class com.imsl.chart.AbstractChartNode
Returns a deep-copy clone of this node.
clone(Object, Map) - Method in class com.imsl.chart.AbstractChartNode
Returns a deep copy of an Object.
clone(Map, Map) - Method in class com.imsl.chart.AbstractChartNode
Returns a deep copy of a Hashtable.
clone(List, Map) - Method in class com.imsl.chart.AbstractChartNode
Returns a deep copy of a vector of ChartNode's.
clone() - Method in class com.imsl.chart.Chart
Returns a clone of the graphics tree.
clone(Map) - Method in class com.imsl.chart.Chart
Returns a clone of this node.
clone() - Method in class com.imsl.chart3d.BufferedPaint
 
clone() - Method in class com.imsl.chart3d.Chart3D
Returns a clone of the graphics tree.
clone(Map) - Method in class com.imsl.chart3d.Chart3D
Returns a clone of this node.
clone() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Clones a copy of the trainer.
clone() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Clones a copy of the trainer.
clone() - Method in class com.imsl.math.DenseLP
Creates and returns a copy of this object.
clone() - Method in class com.imsl.stat.FaureSequence
Returns a copy of this object.
clone() - Method in class com.imsl.stat.MersenneTwister
Returns a clone of this object.
clone() - Method in class com.imsl.stat.MersenneTwister64
Returns a clone of this object.
close() - Method in class com.imsl.io.AbstractFlatFile
Releases this ResultSet object's database and JDBC resources immediately instead of waiting for this to happen when it is automatically closed.
ClusterHierarchical - Class in com.imsl.stat
Performs a hierarchical cluster analysis from a distance matrix.
ClusterHierarchical(double[][]) - Constructor for class com.imsl.stat.ClusterHierarchical
Constructor for ClusterHierarchical.
ClusterKMeans - Class in com.imsl.stat
Perform a K-means (centroid) cluster analysis.
ClusterKMeans(double[][], double[][]) - Constructor for class com.imsl.stat.ClusterKMeans
Constructor for ClusterKMeans.
ClusterKMeans.ClusterNoPointsException - Exception in com.imsl.stat
There is a cluster with no points
ClusterKMeans.ClusterNoPointsException(String) - Constructor for exception com.imsl.stat.ClusterKMeans.ClusterNoPointsException
 
ClusterKMeans.ClusterNoPointsException(String, Object[]) - Constructor for exception com.imsl.stat.ClusterKMeans.ClusterNoPointsException
 
ClusterKMeans.NoConvergenceException - Exception in com.imsl.stat
Convergence did not occur within the maximum number of iterations.
ClusterKMeans.NoConvergenceException(String) - Constructor for exception com.imsl.stat.ClusterKMeans.NoConvergenceException
 
ClusterKMeans.NoConvergenceException(String, Object[]) - Constructor for exception com.imsl.stat.ClusterKMeans.NoConvergenceException
 
coef - Variable in class com.imsl.math.BSpline
The B-spline coefficient array.
coef - Variable in class com.imsl.math.Spline
Coefficients of the piecewise polynomials.
color(double) - Method in interface com.imsl.chart.Colormap
Maps the parameterization interval [0,1] into Colors.
color(double, double, double) - Method in interface com.imsl.chart3d.ColorFunction
 
ColorFunction - Interface in com.imsl.chart3d
Interface to define value dependent colors.
Colormap - Interface in com.imsl.chart
Colormaps are mappings from the unit interval to Colors.
ColormapLegend - Class in com.imsl.chart3d
Adds a legend for a Colormap gradient to the background of the canvas.
ColormapLegend(Chart3D, Colormap, double[]) - Constructor for class com.imsl.chart3d.ColormapLegend
Creates a legend for a Colormap and adds it to the canvas.
ColormapLegend(Chart3D, Colormap, double, double) - Constructor for class com.imsl.chart3d.ColormapLegend
 
COLUMN_APPROXIMATE_MINIMUM_DEGREE - Static variable in class com.imsl.math.ComplexSuperLU
For column ordering, use column approximate minimum degree ordering.
COLUMN_APPROXIMATE_MINIMUM_DEGREE - Static variable in class com.imsl.math.SuperLU
For column ordering, use column approximate minimum degree ordering.
COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatted string for a given column label is to be returned.
COLUMN_SCALING - Static variable in class com.imsl.math.ComplexSuperLU
Indicates that input matrix A was column scaled before factorization.
COLUMN_SCALING - Static variable in class com.imsl.math.SuperLU
Indicates that input matrix A was column scaled before factorization.
COLUMNFIRST - Static variable in class com.imsl.chart.Treemap
Flag to set the treemap orientation drawing columns first.
com.imsl - package com.imsl
 
com.imsl.chart - package com.imsl.chart
 
com.imsl.chart.qc - package com.imsl.chart.qc
 
com.imsl.chart.xml - package com.imsl.chart.xml
 
com.imsl.chart3d - package com.imsl.chart3d
 
com.imsl.datamining - package com.imsl.datamining
 
com.imsl.datamining.neural - package com.imsl.datamining.neural
 
com.imsl.finance - package com.imsl.finance
 
com.imsl.io - package com.imsl.io
 
com.imsl.math - package com.imsl.math
 
com.imsl.stat - package com.imsl.stat
 
compareTo(Object) - Method in class com.imsl.math.Complex
Compares this Complex to another Object.
compareTo(Complex) - Method in class com.imsl.math.Complex
Compares two Complex objects.
complementaryChi(double, double) - Static method in class com.imsl.stat.Cdf
Calculates the complement of the chi-squared cumulative distribution function.
complementaryF(double, double, double) - Static method in class com.imsl.stat.Cdf
Calculates the complement of the F distribution function.
complementaryF2(double, double, double) - Static method in class com.imsl.stat.Cdf
 
complementaryStudentsT(double, double) - Static method in class com.imsl.stat.Cdf
Calculates the complement of the Student's t distribution.
Complex - Class in com.imsl.math
Set of mathematical functions for complex numbers.
Complex(Complex) - Constructor for class com.imsl.math.Complex
Constructs a Complex equal to the argument.
Complex(double, double) - Constructor for class com.imsl.math.Complex
Constructs a Complex with real and imaginary parts given by the input arguments.
Complex(double) - Constructor for class com.imsl.math.Complex
Constructs a Complex with a zero imaginary part.
Complex() - Constructor for class com.imsl.math.Complex
Constructs a Complex equal to zero.
ComplexFFT - Class in com.imsl.math
Complex FFT.
ComplexFFT(int) - Constructor for class com.imsl.math.ComplexFFT
Constructs a complex FFT object.
ComplexLU - Class in com.imsl.math
LU factorization of a matrix of type Complex.
ComplexLU(Complex[][]) - Constructor for class com.imsl.math.ComplexLU
Creates the LU factorization of a square matrix of type Complex.
ComplexMatrix - Class in com.imsl.math
Complex matrix manipulation functions.
ComplexSparseCholesky - Class in com.imsl.math
Sparse Cholesky factorization of a matrix of type ComplexSparseMatrix.
ComplexSparseCholesky(ComplexSparseMatrix) - Constructor for class com.imsl.math.ComplexSparseCholesky
Constructs the matrix structure for the Cholesky factorization of a sparse Hermitian positive definite matrix of type ComplexSparseMatrix.
ComplexSparseCholesky.NotSPDException - Exception in com.imsl.math
The matrix is not Hermitian, positive definite.
ComplexSparseCholesky.NotSPDException() - Constructor for exception com.imsl.math.ComplexSparseCholesky.NotSPDException
 
ComplexSparseCholesky.NumericFactor - Class in com.imsl.math
Data structures and functions for the numeric Cholesky factor.
ComplexSparseCholesky.SymbolicFactor - Class in com.imsl.math
Data structures and functions for the symbolic Cholesky factor.
ComplexSparseMatrix - Class in com.imsl.math
Sparse matrix of type Complex.
ComplexSparseMatrix(int, int) - Constructor for class com.imsl.math.ComplexSparseMatrix
Creates a new instance of ComplexSparseMatrix.
ComplexSparseMatrix(ComplexSparseMatrix) - Constructor for class com.imsl.math.ComplexSparseMatrix
Creates a new instance of ComplexSparseMatrix which is a copy of another ComplexSparseMatrix.
ComplexSparseMatrix(ComplexSparseMatrix.SparseArray) - Constructor for class com.imsl.math.ComplexSparseMatrix
Constructs a complex sparse matrix from a SparseArray object.
ComplexSparseMatrix(int, int, int[][], Complex[][]) - Constructor for class com.imsl.math.ComplexSparseMatrix
Constructs a sparse matrix from SparseArray (Java Sparse Array) data.
ComplexSparseMatrix.SparseArray - Class in com.imsl.math
The SparseArray class uses public fields to hold the data for a sparse matrix in the Java Sparse Array format.
ComplexSparseMatrix.SparseArray() - Constructor for class com.imsl.math.ComplexSparseMatrix.SparseArray
 
ComplexSuperLU - Class in com.imsl.math
Computes the LU factorization of a general sparse matrix of type ComplexSparseMatrix by a column method and solves a sparse linear system of equations Ax=b.
ComplexSuperLU(ComplexSparseMatrix) - Constructor for class com.imsl.math.ComplexSuperLU
Constructor for ComplexSuperLU.
compute(double[], double[]) - Method in interface com.imsl.math.BoundedLeastSquares.Function
Public interface for the user-supplied function to evaluate the function that defines the least-squares problem.
compute(double[], double[]) - Method in interface com.imsl.math.BoundedLeastSquares.Jacobian
Public interface for the user-supplied function to compute the Jacobian.
compute() - Method in class com.imsl.math.CsTCB
Computes the tension-continuity-bias (TCB) cubic spline interpolant.
compute() - Method in class com.imsl.math.Spline2DLeastSquares
Computes a two-dimensional, tensor-product spline approximant using least squares.
compute() - Method in class com.imsl.stat.ANCOVA
Performs one-way analysis of covariance assuming parallelism and returns an array containing the parallelism tests for the one-way analysis of covariance.
compute() - Method in class com.imsl.stat.ANOVAFactorial
Analyzes a balanced factorial design with fixed effects.
compute() - Method in class com.imsl.stat.ARAutoUnivariate
Determines the autoregressive model with the minimum AIC by fitting autoregressive models from 0 to maxlag lags using the method of moments or an estimation method specified by the user through setEstimationMethod.
compute() - Method in class com.imsl.stat.ARMA
Computes least-square estimates of parameters for an ARMA model.
compute() - Method in class com.imsl.stat.ARMAMaxLikelihood
Computes the exact maximum likelihood estimates for the autoregressive and moving average parameters of an ARMA time series
compute(int[]) - Method in class com.imsl.stat.ARMAOutlierIdentification
Detects and determines outliers and simultaneously estimates the model parameters for the given time series.
compute() - Method in class com.imsl.stat.ARSeasonalFit
Computes the minimum AIC and optimum values for s and d based upon the candidates provided in sInitial and dInitial, and computes the values for the transformed series, W_t(s,d).
compute(int) - Method in class com.imsl.stat.AutoARIMA
Estimates potential missing values, detects and determines outliers and simultaneously fits an optimum model from a set of different text{ARIMA}(p,0,0)times(0,d,0)_s models to the outlier free time series.
compute(int[], int[]) - Method in class com.imsl.stat.AutoARIMA
Estimates potential missing values, detects and determines outliers and simultaneously fits an optimum model from a set of different text{ARIMA}(p,0,q)times(0,d,0)_s models to the outlier free time series.
compute(int, int, int, int) - Method in class com.imsl.stat.AutoARIMA
Estimates potential missing values, detects and determines outliers and simultaneously fits an text{ARIMA}(p,0,q)times(0,d,0)_s model to the outlier free time series.
compute() - Method in class com.imsl.stat.ClusterHierarchical
Performs a hierarchical cluster analysis.
compute() - Method in class com.imsl.stat.ClusterKMeans
Computes the cluster means.
compute(int) - Method in class com.imsl.stat.Covariances
Computes the matrix.
compute(double[], int[]) - Method in class com.imsl.stat.Difference
Computes a Difference series.
compute() - Method in class com.imsl.stat.Dissimilarities
Computes a matrix of dissimilarities (or similarities) between the columns (or rows) of a matrix.
compute() - Method in class com.imsl.stat.GARCH
Computes estimates of the parameters of a GARCH(p,q) model.
compute(int, double[], int, int) - Static method in class com.imsl.stat.LackOfFit
Performs lack-of-fit test for a univariate time series or transfer function given the appropriate correlation function using a minimum lag of 1.
compute(int, double[], int, int, int) - Static method in class com.imsl.stat.LackOfFit
Performs lack-of-fit test for a univariate time series or transfer function given the appropriate correlation function.
compute() - Method in class com.imsl.stat.MultipleComparisons
Performs Student-Newman-Keuls multiple comparisons test.
compute(double[][], double[]) - Method in class com.imsl.stat.SelectionRegression
Computes the best multiple linear regression models.
compute(double[][], double[], double[]) - Method in class com.imsl.stat.SelectionRegression
Computes the best weighted multiple linear regression models.
compute(double[][], double[], double[], double[]) - Method in class com.imsl.stat.SelectionRegression
Computes the best weighted multiple linear regression models using frequencies for each observation.
compute(double[][], int) - Method in class com.imsl.stat.SelectionRegression
Computes the best multiple linear regression models using a user-supplied covariance matrix.
compute() - Method in class com.imsl.stat.SignTest
Performs a sign test.
compute() - Method in class com.imsl.stat.StepwiseRegression
Builds the multiple linear regression models using forward selection, backward selection, or stepwise selection.
compute() - Method in class com.imsl.stat.WilcoxonRankSum
Performs a Wilcoxon rank sum test.
computeCoefficients(int, int, FeynmanKac.Boundaries, double[], double[]) - Method in class com.imsl.math.FeynmanKac
Determines the coefficients of the Hermite quintic splines that represent an approximate solution for the Feynman-Kac PDE.
computeForecasts(int) - Method in class com.imsl.stat.ARMAOutlierIdentification
Computes forecasts, associated probability limits and psi weights for an outlier contaminated time series whose underlying outlier free series obeys a general seasonal or non-seasonal ARMA model.
computeLags(int[], int[], double[]) - Method in class com.imsl.datamining.neural.TimeSeriesClassFilter
Computes lags of an array sorted first by class designations and then descending chronological order.
computeLags(int, double[][]) - Method in class com.imsl.datamining.neural.TimeSeriesFilter
Lags time series data to a format used for input to a neural network.
computeMin(MinUncon.Function) - Method in class com.imsl.math.MinUncon
Return the minimum of a smooth function of a single variable of type double using function values only or using function values and derivatives.
computeMin(MinUnconMultiVar.Function) - Method in class com.imsl.math.MinUnconMultiVar
Return the minimum point of a function of n variables of type double using a finite-difference gradient or using a user-supplied gradient.
computeRoots(double[]) - Method in class com.imsl.math.ZeroPolynomial
Computes the roots of the polynomial with real coefficients.
computeRoots(Complex[]) - Method in class com.imsl.math.ZeroPolynomial
Computes the roots of the polynomial with Complex coefficients.
computeStatistics(double[][], int[]) - Method in class com.imsl.datamining.neural.BinaryClassification
Computes the classification error statistics for the supplied network patterns and their associated classifications.
computeStatistics(double[][], int[]) - Method in class com.imsl.datamining.neural.MultiClassification
Computes classification statistics for the supplied network patterns and their associated classifications.
computeStatistics(double[][], double[][]) - Method in class com.imsl.datamining.neural.Network
Computes error statistics.
computeZeros(ZerosFunction.Function) - Method in class com.imsl.math.ZerosFunction
Returns the zeros of a univariate function.
condition(Complex[][]) - Method in class com.imsl.math.ComplexLU
Return an estimate of the reciprocal of the L_1 condition number.
condition(double[][]) - Method in class com.imsl.math.LU
Return an estimate of the reciprocal of the L_1 condition number of a matrix.
confidenceMean(double) - Method in class com.imsl.stat.Summary
Returns the confidence interval for the mean (assuming normality).
confidenceVariance(double) - Method in class com.imsl.stat.Summary
Returns the confidence interval for the variance (assuming normality).
conjugate(Complex) - Static method in class com.imsl.math.Complex
Returns the complex conjugate of a Complex object.
ConjugateGradient - Class in com.imsl.math
Solves a real symmetric definite linear system using the conjugate gradient method with optional preconditioning.
ConjugateGradient(int, ConjugateGradient.Function) - Constructor for class com.imsl.math.ConjugateGradient
Conjugate gradient constructor.
ConjugateGradient.Function - Interface in com.imsl.math
Public interface for the user supplied function to ConjugateGradient.
ConjugateGradient.NoConvergenceException - Exception in com.imsl.math
The conjugate gradient method did not converge within the allowed maximum number of iterations.
ConjugateGradient.NoConvergenceException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NoConvergenceException
 
ConjugateGradient.NoConvergenceException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NoConvergenceException
 
ConjugateGradient.NotDefiniteAMatrixException - Exception in com.imsl.math
The input matrix A is indefinite, that is the matrix is not positive or negative definite.
ConjugateGradient.NotDefiniteAMatrixException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteAMatrixException
 
ConjugateGradient.NotDefiniteAMatrixException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteAMatrixException
 
ConjugateGradient.NotDefiniteJacobiPreconditionerException - Exception in com.imsl.math
The Jacobi preconditioner is not strictly positive or negative definite.
ConjugateGradient.NotDefiniteJacobiPreconditionerException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteJacobiPreconditionerException
 
ConjugateGradient.NotDefiniteJacobiPreconditionerException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteJacobiPreconditionerException
 
ConjugateGradient.NotDefinitePreconditionMatrixException - Exception in com.imsl.math
The Precondition matrix is indefinite.
ConjugateGradient.NotDefinitePreconditionMatrixException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefinitePreconditionMatrixException
 
ConjugateGradient.NotDefinitePreconditionMatrixException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefinitePreconditionMatrixException
 
ConjugateGradient.Preconditioner - Interface in com.imsl.math
Public interface for the user supplied function to ConjugateGradient used for preconditioning.
ConjugateGradient.SingularPreconditionMatrixException - Exception in com.imsl.math
The Precondition matrix is singular.
ConjugateGradient.SingularPreconditionMatrixException(String) - Constructor for exception com.imsl.math.ConjugateGradient.SingularPreconditionMatrixException
 
ConjugateGradient.SingularPreconditionMatrixException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.SingularPreconditionMatrixException
 
conjugateTranspose() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the conjugate transpose of the matrix.
constant(String) - Static method in class com.imsl.math.Physical
Returns the value of a constant, given its name.
constant(String, String) - Static method in class com.imsl.math.Physical
Returns the value of a constant, given its name, in the specified units.
ContingencyTable - Class in com.imsl.stat
Performs a chi-squared analysis of a two-way contingency table.
ContingencyTable(double[][]) - Constructor for class com.imsl.stat.ContingencyTable
Constructs and performs a chi-squared analysis of a two-way contingency table.
CONTINUOUS_VARIABLE - Static variable in class com.imsl.io.MPSReader
Variable is a real number.
Contour - Class in com.imsl.chart
A Contour chart shows level curves of a two-dimensional function.
Contour(AxisXY, double[], double[], double[][], double[]) - Constructor for class com.imsl.chart.Contour
Create a Contour chart from rectangularly gridded data.
Contour(AxisXY, double[], double[], double[][]) - Constructor for class com.imsl.chart.Contour
Create a Contour chart from rectangularly gridded data with computed contour levels.
Contour(AxisXY, double[], double[], double[]) - Constructor for class com.imsl.chart.Contour
Create a Contour chart from scattered data with computed contour levels.
Contour(AxisXY, double[], double[], double[], double[], int) - Constructor for class com.imsl.chart.Contour
Create a Contour chart from scattered data.
Contour.Legend - Class in com.imsl.chart
A legend for a contour chart.
ContourLevel - Class in com.imsl.chart
ContourLevel draws a level curve line and the fill area between the level curve and the next smaller level curve.
ControlLimit - Class in com.imsl.chart.qc
ControlLimit is a control limit line on a process control chart.
convert(Physical, String) - Static method in class com.imsl.math.Physical
Converts a value to a different set of units.
convexity(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the convexity for a security.
copy() - Method in class com.imsl.chart.Chart
Copy the chart to the clipboard.
copyAndSortData(double[], double[]) - Method in class com.imsl.math.Spline
Copy and sort xData into breakPoint and yData into the first column of coef.
copyAndSortData(double[], double[], double[]) - Method in class com.imsl.math.Spline
Copy and sort xData into breakPoint and yData into the first column of coef.
copysign(double, double) - Static method in class com.imsl.math.IEEE
Returns a value with the magnitude of x and with the sign bit of y.
CORRECTED_SSCP_MATRIX - Static variable in class com.imsl.stat.Covariances
Indicates corrected sums of squares and crossproducts matrix.
CORRELATION_COEFFICIENT - Static variable in class com.imsl.stat.Dissimilarities
Indicates the correlation coefficient distance method.
CORRELATION_MATRIX - Static variable in class com.imsl.stat.Covariances
Indicates correlation matrix.
CORRELATION_MATRIX - Static variable in class com.imsl.stat.FactorAnalysis
Indicates correlation matrix.
cos(Complex) - Static method in class com.imsl.math.Complex
Returns the cosine of a Complex.
cos(double) - Static method in class com.imsl.math.JMath
Returns the cosine of a double.
cosh(Complex) - Static method in class com.imsl.math.Complex
Returns the hyperbolic cosh of a Complex.
cosh(double) - Static method in class com.imsl.math.Hyperbolic
Returns the hyperbolic cosine of its argument.
cot(double) - Static method in class com.imsl.math.Sfun
Returns the cotangent of a double.
countTokens() - Method in class com.imsl.io.Tokenizer
Returns the number of times that the nextToken method can be called without generating an exception.
coupdaybs(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the number of days starting with the beginning of the coupon period and ending with the settlement date.
coupdays(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the number of days in the coupon period containing the settlement date.
coupdaysnc(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the number of days starting with the settlement date and ending with the next coupon date.
coupncd(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the first coupon date which follows the settlement date.
coupnum(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the number of coupons payable between the settlement date and the maturity date.
couppcd(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the coupon date which immediately precedes the settlement date.
Covariances - Class in com.imsl.stat
Computes the sample variance-covariance or correlation matrix.
Covariances(double[][]) - Constructor for class com.imsl.stat.Covariances
Constructor for Covariances.
Covariances.NonnegativeFreqException - Exception in com.imsl.stat
Frequencies must be nonnegative.
Covariances.NonnegativeFreqException(String) - Constructor for exception com.imsl.stat.Covariances.NonnegativeFreqException
 
Covariances.NonnegativeFreqException(String, Object[]) - Constructor for exception com.imsl.stat.Covariances.NonnegativeFreqException
 
Covariances.NonnegativeWeightException - Exception in com.imsl.stat
Weights must be nonnegative.
Covariances.NonnegativeWeightException(String) - Constructor for exception com.imsl.stat.Covariances.NonnegativeWeightException
 
Covariances.NonnegativeWeightException(String, Object[]) - Constructor for exception com.imsl.stat.Covariances.NonnegativeWeightException
 
createCharts(Chart, double[][]) - Static method in class com.imsl.chart.qc.XbarR
Creates a combined XbarR chart and RChart from data.
createCharts(Chart, int, double[], double[]) - Static method in class com.imsl.chart.qc.XbarR
Creates a combined XbarR chart and RChart given the means and ranges for a series of equally sized samples.
createCharts(Chart, int[], double[], double[]) - Static method in class com.imsl.chart.qc.XbarR
Creates a combined XbarR chart and RChart given the means and ranges for a series of unequally sized samples.
createCharts(Chart, double[][]) - Static method in class com.imsl.chart.qc.XbarS
Creates a combined XbarS chart and SChart from data.
createCharts(Chart, int, double[], double[]) - Static method in class com.imsl.chart.qc.XbarS
Creates a combined XbarS chart and SChart given the means and in sample standard deviations for a series of equally sized samples.
createCharts(Chart, int[], double[], double[]) - Static method in class com.imsl.chart.qc.XbarS
Creates a combined X-bar chart and S-chart given the means and in sample standard deviations for a series of unequally sized samples.
createContinuousAttribute(ProbabilityDistribution) - Method in class com.imsl.datamining.NaiveBayesClassifier
Create a continuous variable and the associated distribution function.
createContinuousAttribute(ProbabilityDistribution[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Create a continuous variable and the associated distribution functions for each target classification.
createCumulativeLineAxis() - Method in class com.imsl.chart.qc.ParetoChart
Creates a new axis to hold a cumulative line.
createCustomMarker() - Method in interface com.imsl.chart3d.Data.CustomMarkerFactory
Returns a custom marker.
createDataAxis() - Method in class com.imsl.chart.qc.CuSumStatus
Creates a new axis to hold a cummulative line.
createHiddenLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Creates a HiddenLayer.
createHiddenLayer() - Method in class com.imsl.datamining.neural.Network
Creates the next HiddenLayer in the Network.
createInput() - Method in class com.imsl.datamining.neural.InputLayer
Creates an InputNode in the InputLayer of the neural network.
createInputs(int) - Method in class com.imsl.datamining.neural.InputLayer
Creates a number of InputNodes in this Layer of the neural network.
createNominalAttribute(int) - Method in class com.imsl.datamining.NaiveBayesClassifier
Create a nominal attribute and the number of categories
createPerceptron(Activation, double) - Method in class com.imsl.datamining.neural.HiddenLayer
Creates a Perceptron in this Layer with a specified activation function and bias.
createPerceptron() - Method in class com.imsl.datamining.neural.HiddenLayer
Creates a Perceptron in this Layer of the neural network.
createPerceptron(Activation, double) - Method in class com.imsl.datamining.neural.OutputLayer
Creates a Perceptron in this Layer with a specified Activation and bias.
createPerceptron() - Method in class com.imsl.datamining.neural.OutputLayer
Creates a Perceptron in this Layer of the neural network.
createPerceptrons(int) - Method in class com.imsl.datamining.neural.HiddenLayer
Creates a number of Perceptrons in this Layer of the neural network.
createPerceptrons(int, Activation, double) - Method in class com.imsl.datamining.neural.HiddenLayer
Creates a number of Perceptrons in this Layer with the specified bias.
createPerceptrons(int) - Method in class com.imsl.datamining.neural.OutputLayer
Creates a number of Perceptrons in this Layer of the neural network.
createPerceptrons(int, Activation, double) - Method in class com.imsl.datamining.neural.OutputLayer
Creates a number of Perceptrons in this Layer with specified activation and bias.
CrossCorrelation - Class in com.imsl.stat
Computes the sample cross-correlation function of two stationary time series.
CrossCorrelation(double[], double[], int) - Constructor for class com.imsl.stat.CrossCorrelation
Constructor to compute the sample cross-correlation function of two stationary time series.
CrossCorrelation.NonPosVariancesException - Exception in com.imsl.stat
The problem is ill-conditioned.
CrossCorrelation.NonPosVariancesException(String) - Constructor for exception com.imsl.stat.CrossCorrelation.NonPosVariancesException
 
CrossCorrelation.NonPosVariancesException(String, Object[]) - Constructor for exception com.imsl.stat.CrossCorrelation.NonPosVariancesException
 
crosshatch(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a horizonal and vertical crosshatch pattern.
CsAkima - Class in com.imsl.math
Extension of the Spline class to handle the Akima cubic spline.
CsAkima(double[], double[]) - Constructor for class com.imsl.math.CsAkima
Constructs the Akima cubic spline interpolant to the given data points.
CsInterpolate - Class in com.imsl.math
Extension of the Spline class to interpolate data points.
CsInterpolate(double[], double[]) - Constructor for class com.imsl.math.CsInterpolate
Constructs a cubic spline that interpolates the given data points.
CsInterpolate(double[], double[], int, double, int, double) - Constructor for class com.imsl.math.CsInterpolate
Constructs a cubic spline that interpolates the given data points with specified derivative endpoint conditions.
CsPeriodic - Class in com.imsl.math
Extension of the Spline class to interpolate data points with periodic boundary conditions.
CsPeriodic(double[], double[]) - Constructor for class com.imsl.math.CsPeriodic
Constructs a cubic spline that interpolates the given data points with periodic boundary conditions.
CsShape - Class in com.imsl.math
Extension of the Spline class to interpolate data points consistent with the concavity of the data.
CsShape(double[], double[]) - Constructor for class com.imsl.math.CsShape
Construct a cubic spline interpolant which is consistent with the concavity of the data.
CsShape.TooManyIterationsException - Exception in com.imsl.math
Too many iterations.
CsShape.TooManyIterationsException() - Constructor for exception com.imsl.math.CsShape.TooManyIterationsException
 
CsShape.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.math.CsShape.TooManyIterationsException
 
CsShape.TooManyIterationsException(Object[]) - Constructor for exception com.imsl.math.CsShape.TooManyIterationsException
 
CsSmooth - Class in com.imsl.math
Extension of the Spline class to construct a smooth cubic spline from noisy data points.
CsSmooth(double[], double[]) - Constructor for class com.imsl.math.CsSmooth
Constructs a smooth cubic spline from noisy data using cross-validation to estimate the smoothing parameter.
CsSmooth(double[], double[], double[]) - Constructor for class com.imsl.math.CsSmooth
Constructs a smooth cubic spline from noisy data using cross-validation to estimate the smoothing parameter.
CsSmoothC2 - Class in com.imsl.math
Extension of the Spline class used to construct a spline for noisy data points using an alternate method.
CsSmoothC2(double[], double[], double) - Constructor for class com.imsl.math.CsSmoothC2
Constructs a smooth cubic spline from noisy data using an algorithm based on Reinsch (1967).
CsSmoothC2(double[], double[], double[], double) - Constructor for class com.imsl.math.CsSmoothC2
Constructs a smooth cubic spline from noisy data using an algorithm based on Reinsch (1967) with weights supplied by the user.
CsTCB - Class in com.imsl.math
Extension of the Spline class to handle a tension-continuity-bias (TCB) cubic spline, also known as a Kochanek-Bartels spline and is a generalization of the Catmull-Rom spline.
CsTCB(double[], double[]) - Constructor for class com.imsl.math.CsTCB
Constructs the tension-continuity-bias (TCB) cubic spline interpolant to the given data points.
CUBIC_SPLINE - Static variable in class com.imsl.stat.ARMAEstimateMissing
Indicates that missing values should be estimated using cublic spline interpolation.
cumipmt(double, int, double, int, int, int) - Static method in class com.imsl.finance.Finance
Returns the cumulative interest paid between two periods.
cumprinc(double, int, double, int, int, int) - Static method in class com.imsl.finance.Finance
Returns the cumulative principal paid between two periods.
CURRENT - Static variable in class com.imsl.math.Physical
 
currentType - Variable in class com.imsl.chart.Draw
 
CuSum - Class in com.imsl.chart.qc
CuSum is a cumulative sum chart.
CuSum(AxisXY, double[]) - Constructor for class com.imsl.chart.qc.CuSum
Creates a CuSum chart given the means of a series of samples.
CuSumStatus - Class in com.imsl.chart.qc
CuSumStatus is a cumulative sum status chart.
CuSumStatus(AxisXY, double[], double, double) - Constructor for class com.imsl.chart.qc.CuSumStatus
Creates a CuSumStatus chart.

D

d2 - Static variable in class com.imsl.chart.qc.ShewhartControlChart
This field contains d_{2,n} the mean of the ranges of n samples from a Gaussian distribution.
d3 - Static variable in class com.imsl.chart.qc.ShewhartControlChart
This field contains d_{3,n} the standard deviation of the ranges of n samples from a Gaussian distribution.
DASH_PATTERN_DASH - Static variable in class com.imsl.chart.ChartNode
Flag to draw a dashed line.
DASH_PATTERN_DASH_DOT - Static variable in class com.imsl.chart.ChartNode
Flag to draw a dash-dot pattern line.
DASH_PATTERN_DOT - Static variable in class com.imsl.chart.ChartNode
Flag to draw a dotted line.
DASH_PATTERN_SOLID - Static variable in class com.imsl.chart.ChartNode
Flag to draw solid line.
Data - Class in com.imsl.chart
Draws a data node.
Data(ChartNode) - Constructor for class com.imsl.chart.Data
Creates a data node.
Data(ChartNode, double[]) - Constructor for class com.imsl.chart.Data
Creates a data node with y values.
Data(ChartNode, ChartFunction, double, double) - Constructor for class com.imsl.chart.Data
Creates a data node with y values.
Data(ChartNode, double[], double[]) - Constructor for class com.imsl.chart.Data
Creates a data node with x and y values.
Data - Class in com.imsl.chart3d
Draws a 3D data node.
Data(AxisXYZ) - Constructor for class com.imsl.chart3d.Data
Creates a data node.
Data(AxisXYZ, double[], double[], double[]) - Constructor for class com.imsl.chart3d.Data
Creates a data node with x, y and z values.
Data.CustomMarkerFactory - Interface in com.imsl.chart3d
Factory to create customized markers.
DATA_TYPE_ERROR_X - Static variable in class com.imsl.chart.ErrorBar
Value for attribute "DataType" indicating that this is a horizontal error bar.
DATA_TYPE_ERROR_Y - Static variable in class com.imsl.chart.ErrorBar
Value for attribute "DataType" indicating that this is a vertical error bar.
DATA_TYPE_FILL - Static variable in class com.imsl.chart.ChartNode
Value for attribute "DataType" indicating that the area between the lines connecting the data points and the horizontal reference line (y = attribute "Reference") should be filled.
DATA_TYPE_LINE - Static variable in class com.imsl.chart.ChartNode
Value for attribute "DataType" indicating that the data points should be connected with line segments.
DATA_TYPE_LINE - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "DataType" indicating that the data points should be connected with line segments.
DATA_TYPE_MARKER - Static variable in class com.imsl.chart.ChartNode
Value for attribute "DataType" indicating that a marker should be drawn at each data point.
DATA_TYPE_MARKER - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "DataType" indicating that a marker should be drawn at each data point.
DATA_TYPE_PICTURE - Static variable in class com.imsl.chart.ChartNode
Value for attribute "DataType" indicating that an image (attribute "Image") should be drawn at each data point.
DATA_TYPE_PICTURE - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "DataType" indicating that an image (attribute "Image") should be drawn at each data point.
DATA_TYPE_TUBE - Static variable in class com.imsl.chart.ChartNode
Value for attribute "DataType" indicating that an a tube connecting the data points should be drawn.
DATA_TYPE_TUBE - Static variable in class com.imsl.chart3d.ChartNode3D
Value for attribute "DataType" indicating that a tube connecting the data points should be drawn.
dataRange(double[]) - Method in class com.imsl.chart.Bar
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.BarItem
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.BarSet
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.BoxPlot
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Contour
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Data
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Dendrogram
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.ErrorBar
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Heatmap
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.HighLowClose
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.qc.ControlLimit
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.qc.CuSum
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.qc.ShewhartControlChart
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Treemap
Updates the data range, range = {xmin,xmax,ymin,ymax} or range = {xmin,xmax,ymin,ymax,zmin,zmax}.
dataRange(double[]) - Method in class com.imsl.chart3d.Data
Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart3d.Surface
Update the data range, range = {xmin,xmax,ymin,ymax}.
DAY - Static variable in class com.imsl.chart.HighLowClose
Milliseconds per day
DayCountBasis - Class in com.imsl.finance
The Day Count Basis.
DayCountBasis(BasisPart, BasisPart) - Constructor for class com.imsl.finance.DayCountBasis
Creates a new DayCountBasis.
daysBetween(GregorianCalendar, GregorianCalendar) - Method in interface com.imsl.finance.BasisPart
Returns the number of days from date1 to date2.
daysInPeriod(GregorianCalendar, int) - Method in interface com.imsl.finance.BasisPart
Returns the number of days in a coupon period.
db(double, double, int, int, int) - Static method in class com.imsl.finance.Finance
Returns the depreciation of an asset using the fixed-declining balance method.
ddb(double, double, int, int, double) - Static method in class com.imsl.finance.Finance
Returns the depreciation of an asset using the double-declining balance method.
decode(double) - Method in class com.imsl.datamining.neural.ScaleFilter
Unscales a value.
decode(double[]) - Method in class com.imsl.datamining.neural.ScaleFilter
Unscales an array of values.
decode(int, double[][]) - Method in class com.imsl.datamining.neural.ScaleFilter
Unscales a single column of a two dimensional array of values.
decode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter
Decodes a binary encoded array into its nominal category.
decode(int[][]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter
Decodes a matrix representing the binary encoded columns of the nominal variable.
decode(double) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Decodes an encoded ordinal variable.
decode(double[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Decodes an array of encoded ordinal values.
defineConstant(String, Physical) - Static method in class com.imsl.math.Physical
Defines a new constant.
definePrefix(String, double) - Static method in class com.imsl.math.Physical
Defines a new prefix.
defineUnit(String, Physical) - Static method in class com.imsl.math.Physical
Defines a new unit.
deleteRow() - Method in class com.imsl.io.AbstractFlatFile
Deletes the current row from this ResultSet object and from the underlying database.
Dendrogram - Class in com.imsl.chart
A Dendrogram chart for cluster analysis.
Dendrogram(AxisXY, ClusterHierarchical) - Constructor for class com.imsl.chart.Dendrogram
Constructs a vertical dendrogram chart using supplied ClusterHierarchical object.
Dendrogram(AxisXY, double[], int[], int[]) - Constructor for class com.imsl.chart.Dendrogram
Constructs a vertical dendrogram chart using supplied data.
Dendrogram(AxisXY, ClusterHierarchical, int) - Constructor for class com.imsl.chart.Dendrogram
Constructs a dendrogram chart using supplied ClusterHierarchical object.
Dendrogram(AxisXY, double[], int[], int[], int) - Constructor for class com.imsl.chart.Dendrogram
Constructs a dendrogram chart using supplied data.
DENDROGRAM_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.ChartNode
Flag to indicate a horizontal dendrogram.
DENDROGRAM_TYPE_VERTICAL - Static variable in class com.imsl.chart.ChartNode
Flag to indicate a vertical dendrogram.
DenseLP - Class in com.imsl.math
Solves a linear programming problem using an active set strategy.
DenseLP(MPSReader) - Constructor for class com.imsl.math.DenseLP
Constructor using an MPSReader object.
DenseLP(double[][], double[], double[]) - Constructor for class com.imsl.math.DenseLP
Constructor variables of type double.
DenseLP.AllConstraintsNotSatisfiedException - Exception in com.imsl.math
All constraints are not satisfied.
DenseLP.AllConstraintsNotSatisfiedException() - Constructor for exception com.imsl.math.DenseLP.AllConstraintsNotSatisfiedException
All constraints are not satisfied.
DenseLP.AllConstraintsNotSatisfiedException(String) - Constructor for exception com.imsl.math.DenseLP.AllConstraintsNotSatisfiedException
All constraints are not satisfied.
DenseLP.AllConstraintsNotSatisfiedException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.AllConstraintsNotSatisfiedException
All constraints are not satisfied.
DenseLP.BoundsInconsistentException - Exception in com.imsl.math
The bounds given are inconsistent.
DenseLP.BoundsInconsistentException(String) - Constructor for exception com.imsl.math.DenseLP.BoundsInconsistentException
The bounds given are inconsistent.
DenseLP.BoundsInconsistentException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.BoundsInconsistentException
The bounds given are inconsistent.
DenseLP.CyclingOccurringException - Exception in com.imsl.math
The algorithm appears to be cycling.
DenseLP.CyclingOccurringException() - Constructor for exception com.imsl.math.DenseLP.CyclingOccurringException
The algorithm appears to be cycling.
DenseLP.CyclingOccurringException(String) - Constructor for exception com.imsl.math.DenseLP.CyclingOccurringException
The algorithm appears to be cycling.
DenseLP.CyclingOccurringException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.CyclingOccurringException
The algorithm appears to be cycling.
DenseLP.MultipleSolutionsException - Exception in com.imsl.math
The problem has multiple solutions giving essentially the same minimum.
DenseLP.MultipleSolutionsException() - Constructor for exception com.imsl.math.DenseLP.MultipleSolutionsException
The problem has multiple solutions giving essentially the same minimum.
DenseLP.MultipleSolutionsException(String) - Constructor for exception com.imsl.math.DenseLP.MultipleSolutionsException
The problem has multiple solutions giving essentially the same minimum.
DenseLP.MultipleSolutionsException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.MultipleSolutionsException
The problem has multiple solutions giving essentially the same minimum.
DenseLP.NoAcceptablePivotException - Exception in com.imsl.math
No acceptable pivot could be found.
DenseLP.NoAcceptablePivotException() - Constructor for exception com.imsl.math.DenseLP.NoAcceptablePivotException
No acceptable pivot could be found.
DenseLP.NoAcceptablePivotException(String) - Constructor for exception com.imsl.math.DenseLP.NoAcceptablePivotException
No acceptable pivot could be found.
DenseLP.NoAcceptablePivotException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.NoAcceptablePivotException
No acceptable pivot could be found.
DenseLP.ProblemUnboundedException - Exception in com.imsl.math
The problem is unbounded.
DenseLP.ProblemUnboundedException() - Constructor for exception com.imsl.math.DenseLP.ProblemUnboundedException
The problem is unbounded.
DenseLP.ProblemUnboundedException(String) - Constructor for exception com.imsl.math.DenseLP.ProblemUnboundedException
The problem is unbounded.
DenseLP.ProblemUnboundedException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.ProblemUnboundedException
The problem is unbounded.
DenseLP.ProblemVacuousException - Exception in com.imsl.math
The problem is vaxuous.
DenseLP.ProblemVacuousException() - Constructor for exception com.imsl.math.DenseLP.ProblemVacuousException
The problem is vaxuous.
DenseLP.ProblemVacuousException(String) - Constructor for exception com.imsl.math.DenseLP.ProblemVacuousException
The problem is vaxuous.
DenseLP.ProblemVacuousException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.ProblemVacuousException
The problem is vaxuous.
DenseLP.SomeConstraintsDiscardedException - Exception in com.imsl.math
Some constraints were discarded because they were too linearly dependent on other active constraints.
DenseLP.SomeConstraintsDiscardedException() - Constructor for exception com.imsl.math.DenseLP.SomeConstraintsDiscardedException
Some constraints were discarded because they were too linearly dependent on other active constraints.
DenseLP.SomeConstraintsDiscardedException(String) - Constructor for exception com.imsl.math.DenseLP.SomeConstraintsDiscardedException
Some constraints were discarded because they were too linearly dependent on other active constraints.
DenseLP.SomeConstraintsDiscardedException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.SomeConstraintsDiscardedException
Some constraints were discarded because they were too linearly dependent on other active constraints.
derivative(double, double) - Method in interface com.imsl.datamining.neural.Activation
Returns the value of the derivative of the activation function.
derivative(double) - Method in class com.imsl.math.BSpline
Returns the value of the first derivative of the B-spline at a point.
derivative(double, int) - Method in class com.imsl.math.BSpline
Returns the value of the derivative of the B-spline at a point.
derivative(double[], int) - Method in class com.imsl.math.BSpline
Returns the value of the derivative of the B-spline at each point of an array.
derivative(double) - Method in class com.imsl.math.Spline
Returns the value of the first derivative of the spline at a point.
derivative(double, int) - Method in class com.imsl.math.Spline
Returns the value of the derivative of the spline at a point.
derivative(double[], int) - Method in class com.imsl.math.Spline
Returns the value of the derivative of the spline at each point of an array.
derivative(double, double, int, int) - Method in class com.imsl.math.Spline2D
Returns the value of the partial derivative of the tensor-product spline at the point (x, y).
derivative(double[], double[], int, int) - Method in class com.imsl.math.Spline2D
Returns the values of the partial derivative of the tensor-product spline of an array of points.
derivative(double[], int, double[], double[], double[]) - Method in interface com.imsl.stat.NonlinearRegression.Derivative
Computes the weight, frequency, and partial derivatives of the residual given the parameter vector theta for a single observation.
descending(int[]) - Static method in class com.imsl.stat.Sort
Function to sort an integer array into descending order.
descending(int[], int[]) - Static method in class com.imsl.stat.Sort
Sort an integer array into descending order and returns the permutation vector.
descending(double[]) - Static method in class com.imsl.stat.Sort
Sort an array into descending order.
descending(double[], int[]) - Static method in class com.imsl.stat.Sort
Sort an array into descending order and returns the permutation vector.
descending(double[][], int) - Static method in class com.imsl.stat.Sort
Function to sort a matrix into descending order by the first nkeys.
descending(double[][], int[]) - Static method in class com.imsl.stat.Sort
Function to sort a matrix into descending order by specified keys.
descending(double[][], int, int[]) - Static method in class com.imsl.stat.Sort
Function to sort an array into descending order by the first nkeys and returns the permutation vector.
descending(double[][], int[], int[]) - Static method in class com.imsl.stat.Sort
Function to sort a matrix into descending order by specified keys and return the permutation vector.
determinant() - Method in class com.imsl.math.ComplexLU
Return the determinant of the matrix used to construct this instance.
determinant() - Method in class com.imsl.math.LU
Return the determinant of the matrix used to construct this instance.
diagonal(int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a diagonal pattern.
diamond(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a diamond pattern (a checkerboard rotated 45 degrees).
diamondHatch(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a crosshatch on a 45 degree angle.
Difference - Class in com.imsl.stat
Differences a seasonal or nonseasonal time series.
Difference() - Constructor for class com.imsl.stat.Difference
Constructor for Difference.
dim - Variable in class com.imsl.math.Physical
 
DIRECT_AT_RESTART_AND_TERMINATION - Static variable in class com.imsl.math.GenMinRes
Indicates residual updating is to be done by direct evaluation upon restarting and at termination.
DIRECT_AT_RESTART_ONLY - Static variable in class com.imsl.math.GenMinRes
Indicates residual updating is to be done by direct evaluation upon restarting only.
DirectionalLight - Class in com.imsl.chart3d
A directional light.
DirectionalLight(Chart3D) - Constructor for class com.imsl.chart3d.DirectionalLight
Creates a directional light pointing in the negative z direction.
DirectionalLight(Chart3D, double, double, double) - Constructor for class com.imsl.chart3d.DirectionalLight
Creates a directional light pointing with a specified direction.
disc(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the implied interest rate of a discount bond.
discreteUniform(int, int) - Static method in class com.imsl.stat.Cdf
Evaluates the discrete uniform cumulative probability distribution function.
discreteUniform(double, int) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the discrete uniform cumulative probability distribution function.
discreteUniform(int, int) - Static method in class com.imsl.stat.Pdf
Evaluates the discrete uniform probability density function.
DiscriminantAnalysis - Class in com.imsl.stat
Performs a linear or a quadratic discriminant function analysis among several known groups.
DiscriminantAnalysis(int, int) - Constructor for class com.imsl.stat.DiscriminantAnalysis
Constructs a DiscriminantAnalysis.
DiscriminantAnalysis.CovarianceSingularException - Exception in com.imsl.stat
The variance-covariance matrix is singular.
DiscriminantAnalysis.CovarianceSingularException(String) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException
The variance-covariance matrix is singular.
DiscriminantAnalysis.CovarianceSingularException(String, Object[]) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException
The variance-covariance matrix is singular.
DiscriminantAnalysis.EmptyGroupException - Exception in com.imsl.stat
There are no observations in a group.
DiscriminantAnalysis.EmptyGroupException(String) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.EmptyGroupException
There are no observations in a group.
DiscriminantAnalysis.EmptyGroupException(String, Object[]) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.EmptyGroupException
There are no observations in a group.
DiscriminantAnalysis.SumOfWeightsNegException - Exception in com.imsl.stat
The sum of the weights have become negative.
DiscriminantAnalysis.SumOfWeightsNegException(String) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException
The sum of the weights have become negative.
DiscriminantAnalysis.SumOfWeightsNegException(String, Object[]) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException
The sum of the weights have become negative.
Dissimilarities - Class in com.imsl.stat
Computes a matrix of dissimilarities (or similarities) between the columns (or rows) of a matrix.
Dissimilarities(double[][]) - Constructor for class com.imsl.stat.Dissimilarities
Constructor for Dissimilarities.
Dissimilarities.NoPositiveVarianceException - Exception in com.imsl.stat
No variable has positive variance.
Dissimilarities.NoPositiveVarianceException() - Constructor for exception com.imsl.stat.Dissimilarities.NoPositiveVarianceException
Constructs a NoPositiveVarianceException.
Dissimilarities.ScaleFactorZeroException - Exception in com.imsl.stat
The computations cannot continue because a scale factor is zero.
Dissimilarities.ScaleFactorZeroException(int) - Constructor for exception com.imsl.stat.Dissimilarities.ScaleFactorZeroException
Constructs a ScaleFactorZeroException.
Dissimilarities.ZeroNormException - Exception in com.imsl.stat
The computations cannot continue because the Euclidean norm of the column is equal to zero.
Dissimilarities.ZeroNormException(int) - Constructor for exception com.imsl.stat.Dissimilarities.ZeroNormException
Constructs a ZeroNormException.
Distribution - Interface in com.imsl.stat
Public interface for the user-supplied distribution function.
divide(Complex, Complex) - Static method in class com.imsl.math.Complex
Returns the result of a Complex object divided by a Complex object, x/y.
divide(Complex, double) - Static method in class com.imsl.math.Complex
Returns the result of a Complex object divided by a double, x/y.
divide(double, Complex) - Static method in class com.imsl.math.Complex
Returns the result of a double divided by a Complex object, x/y.
divide(Physical, Physical) - Static method in class com.imsl.math.Physical
Divide two Physical objects.
divide(Physical, double) - Static method in class com.imsl.math.Physical
Divide a Physical object by a double.
divide(double, Physical) - Static method in class com.imsl.math.Physical
Divide a double by a Physical object.
doGet(HttpServletRequest, HttpServletResponse) - Method in class com.imsl.chart.ChartServlet
Returns the chart as a PNG image.
doGetBytes(int) - Method in class com.imsl.io.AbstractFlatFile
Implements the actual getBytes().
doGetBytes(int) - Method in class com.imsl.io.FlatFile
Gets the value of the designated column in the current row as a byte array.
dollarde(double, int) - Static method in class com.imsl.finance.Finance
Converts a fractional price to a decimal price.
dollarfr(double, int) - Static method in class com.imsl.finance.Finance
Converts a decimal price to a fractional price.
doNext() - Method in class com.imsl.io.AbstractFlatFile
Implements the operations on the file required by the method next().
doNext() - Method in class com.imsl.io.FlatFile
Moves the cursor down one row from its current position.
dot(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a pattern that is an array of circles.
doubleValue() - Method in class com.imsl.math.Complex
Returns the value of the real part as a double.
doubleValue() - Method in class com.imsl.math.Physical
Returns the value of this dimensionless object.
downdate(double[]) - Method in class com.imsl.math.Cholesky
Downdates the factorization by subtracting a rank-1 matrix.
downdate(double[][], int[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Removes a set of observations from the discriminant functions.
downdate(double[][], int[], int[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Removes a set of observations from the discriminant functions.
downdate(double[][], int[], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Removes a set of observations and associated frequencies and weights from the discriminant functions.
downdate(double[][], int[], int[], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Removes a set of observations and associated frequencies and weights from the discriminant functions.
downdateX(double[]) - Method in class com.imsl.stat.NormTwoSample
Removes the observations in x from the first sample.
downdateY(double[]) - Method in class com.imsl.stat.NormTwoSample
Removes the observations in y from the second sample.
Draw - Class in com.imsl.chart
Chart tree renderer.
Draw(Graphics, Dimension) - Constructor for class com.imsl.chart.Draw
Contructs a Draw object.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.Draw
Draws the outline of a circular or elliptical arc covering the specified rectangle.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawMap
Draws the outline of a circular or elliptical arc covering the specified rectangle.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawPick
Draw an arc.
drawClippedImage(Image, int, int) - Method in class com.imsl.chart.Draw
Draws an image such that any portion of the image beyond the axis range is clipped.
drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.Draw
Draw an error bar.
drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.DrawMap
Draw an error bar.
drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.DrawPick
Draw ErrorBar
drawImage(Image, int, int) - Method in class com.imsl.chart.Draw
Draw an image.
drawImage(Image, int, int) - Method in class com.imsl.chart.DrawMap
Draw Image
drawImage(Image, int, int) - Method in class com.imsl.chart.DrawPick
Draw Image
drawLine(int, int, int, int) - Method in class com.imsl.chart.Draw
Draw a line from (x0,y0) to (x1,y1).
drawLine(int, int, int, int) - Method in class com.imsl.chart.DrawMap
Draw a line from (x0,y0) to (x1,y1).
drawLine(int, int, int, int) - Method in class com.imsl.chart.DrawPick
Draw a line from (x0,y0) to (x1,y1).
DrawMap - Class in com.imsl.chart
Creates an HTML client-side imagemap from a chart tree.
DrawMap(Graphics, Dimension) - Constructor for class com.imsl.chart.DrawMap
Contructs a DrawMap object.
drawMarker(int, int) - Method in class com.imsl.chart.Draw
Draw a marker.
drawMarker(int, int) - Method in class com.imsl.chart.DrawMap
Draw a marker.
drawMarker(int, int) - Method in class com.imsl.chart.DrawPick
Draw a marker.
DrawPick - Class in com.imsl.chart
The DrawPick class.
DrawPick(MouseEvent, Graphics, Dimension) - Constructor for class com.imsl.chart.DrawPick
Contructs a DrawPick object.
drawRotatedText(Text, int, int, float) - Method in class com.imsl.chart.Draw
Draws a text object, at the specified angle, with its lower left point being at (x,y).
drawText(Text, int, int) - Method in class com.imsl.chart.Draw
Draws a text object.
drawText(Text, int, int, boolean) - Method in class com.imsl.chart.Draw
Draws a text object.
drawText(Graphics, Text) - Method in class com.imsl.chart.Draw
Draws the text.
drawText(Text, int, int, boolean) - Method in class com.imsl.chart.DrawMap
 
drawText(Text, int, int) - Method in class com.imsl.chart.DrawPick
 
Dummy - Class in com.imsl
 
Dummy() - Constructor for class com.imsl.Dummy
 
DUNN_SIDAK - Static variable in class com.imsl.stat.ANOVA
The Dunn-Sidak method
duration(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the Macauley's duration of a security where the security has periodic interest payments.

E

E - Static variable in class com.imsl.math.JMath
 
effect(double, int) - Static method in class com.imsl.finance.Finance
Returns the effective annual interest rate.
Eigen - Class in com.imsl.math
Collection of Eigen System functions.
Eigen() - Constructor for class com.imsl.math.Eigen
Constructs the eigenvalues and the eigenvectors of a real square matrix.
Eigen.DidNotConvergeException - Exception in com.imsl.math
The iteration did not converge
Eigen.DidNotConvergeException(String) - Constructor for exception com.imsl.math.Eigen.DidNotConvergeException
 
Eigen.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.math.Eigen.DidNotConvergeException
 
EmpiricalQuantiles - Class in com.imsl.stat
Computes empirical quantiles.
EmpiricalQuantiles(double[], double[]) - Constructor for class com.imsl.stat.EmpiricalQuantiles
Constructor for EmpiricalQuantiles.
EmpiricalQuantiles.ScaleFactorZeroException - Exception in com.imsl.stat
The computations cannot continue because a scale factor is zero.
EmpiricalQuantiles.ScaleFactorZeroException(int) - Constructor for exception com.imsl.stat.EmpiricalQuantiles.ScaleFactorZeroException
Constructs a ScaleFactorZeroException.
encode(double) - Method in class com.imsl.datamining.neural.ScaleFilter
Scales a value.
encode(double[]) - Method in class com.imsl.datamining.neural.ScaleFilter
Scales an array of values.
encode(int, double[][]) - Method in class com.imsl.datamining.neural.ScaleFilter
Scales a single column of a two dimensional array of values.
encode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter
Encodes class data prior to its use in neural network training.
encode(int) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter
Apply forward encoding to a value.
encode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Encodes an array of ordinal categories into an array of transformed percentages.
encode(int) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Encodes an ordinal category.
END_COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a column label is to be returned.
END_COLUMN_LABELS - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a column label row is to be returned.
END_ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatted string for ending an entry is to be returned.
END_MATRIX - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a matrix is to be returned.
END_ROW - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a row is to be returned.
END_ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatting string for ending a row label is to be returned.
endErrorBar() - Method in class com.imsl.chart.Draw
Stop drawing an error bar.
endErrorBar() - Method in class com.imsl.chart.DrawMap
 
endErrorBar() - Method in class com.imsl.chart.DrawPick
End ErrorBar
endFill() - Method in class com.imsl.chart.Draw
Stop drawing a filled region.
endFill() - Method in class com.imsl.chart.DrawMap
 
endFill() - Method in class com.imsl.chart.DrawPick
End fill
endImage() - Method in class com.imsl.chart.Draw
Stop drawing an image.
endImage() - Method in class com.imsl.chart.DrawMap
 
endImage() - Method in class com.imsl.chart.DrawPick
End Image
endLine() - Method in class com.imsl.chart.Draw
Finish drawing lines.
endLine() - Method in class com.imsl.chart.DrawMap
 
endLine() - Method in class com.imsl.chart.DrawPick
Finish drawing lines.
endMarker() - Method in class com.imsl.chart.Draw
Finish drawing markers.
endMarker() - Method in class com.imsl.chart.DrawMap
 
endMarker() - Method in class com.imsl.chart.DrawPick
Finish drawing markers.
endText() - Method in class com.imsl.chart.Draw
Stop drawing text.
endText() - Method in class com.imsl.chart.DrawMap
 
endText() - Method in class com.imsl.chart.DrawPick
End Text
ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatted string for a given entry is to be returned.
EpochTrainer - Class in com.imsl.datamining.neural
Two-stage training using randomly selected training patterns in stage I.
EpochTrainer(Trainer) - Constructor for class com.imsl.datamining.neural.EpochTrainer
Creates a single stage EpochTrainer.
EpochTrainer(Trainer, Trainer) - Constructor for class com.imsl.datamining.neural.EpochTrainer
Creates an two-stage EpochTrainer.
EPSILON_LARGE - Static variable in class com.imsl.math.Sfun
The largest relative spacing for doubles.
EPSILON_LARGE - Static variable in class com.imsl.math.Spline
The largest relative spacing for double.
EPSILON_SMALL - Static variable in class com.imsl.math.QuadraticProgramming
The smallest relative spacing for doubles.
EPSILON_SMALL - Static variable in class com.imsl.math.Sfun
The smallest relative spacing for doubles.
EPSILON_SMALL - Static variable in class com.imsl.math.ZeroPolynomial
The smallest relative spacing for doubles.
EpsilonAlgorithm - Class in com.imsl.math
The class is used to determine the limit of a sequence of approximations, by means of the Epsilon algorithm of P.
EpsilonAlgorithm() - Constructor for class com.imsl.math.EpsilonAlgorithm
Initializes an EpsilonAlgorithm with a maximum table size of 50.
EpsilonAlgorithm(int) - Constructor for class com.imsl.math.EpsilonAlgorithm
Initializes an EpsilonAlgorithm.
equals(Complex) - Method in class com.imsl.math.Complex
Compares with another Complex.
equals(Object) - Method in class com.imsl.math.Complex
Compares this object against the specified object.
erf(double) - Static method in class com.imsl.math.Sfun
Returns the error function of a double.
erfc(double) - Static method in class com.imsl.math.Sfun
Returns the complementary error function of a double.
erfce(double) - Static method in class com.imsl.math.Sfun
Returns the exponentially scaled complementary error function.
erfcInverse(double) - Static method in class com.imsl.math.Sfun
Returns the inverse of the complementary error function.
erfInverse(double) - Static method in class com.imsl.math.Sfun
Returns the inverse of the error function.
error(String, Object[]) - Method in class com.imsl.chart.xml.ChartXML
Handles error messages.
error(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML
Receive notification of a recoverable error.
error(double[], double[]) - Method in interface com.imsl.datamining.neural.QuasiNewtonTrainer.Error
Returns the contribution to the error from a single training output target.
ERROR_BAR - Static variable in class com.imsl.chart.Draw
 
ERROR_NORM_ABS - Static variable in class com.imsl.math.ODE
Used by method setNorm to indicate that the error norm to be used is to be the absolute error, equals max(|e_i|)
ERROR_NORM_EUCLIDEAN - Static variable in class com.imsl.math.ODE
Used by method setNorm to indicate that the error norm to be used is to be the scaled Euclidean norm defined as

{s = sqrt {sum_{i=1}^{neq}{frac{{e_i}^2}{{w_i}^2}}}}

ERROR_NORM_MAX - Static variable in class com.imsl.math.ODE
Used by method setNorm to indicate that the error norm to be used is to be the maximum of e_i/max(|y_i(t)|, floor) where floor is set via setFloor
ERROR_NORM_MINABSREL - Static variable in class com.imsl.math.ODE
Used by method setNorm to indicate that the error norm to be used is to be the minimum of the absolute error and the relative error, equals the maximum of e_i/max(|y_i(t)|, 1)
ErrorBar - Class in com.imsl.chart
Data points with error bars.
ErrorBar(AxisXY, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.ErrorBar
Creates a set of error bars centered at (x[k],y[k]) and with extents low[k],high[k].
errorGradient(double[], double[]) - Method in interface com.imsl.datamining.neural.QuasiNewtonTrainer.Error
Returns the derivative of the error function with respect to the forecast output.
eval(HyperRectangleQuadrature.Function) - Method in class com.imsl.math.HyperRectangleQuadrature
Returns the value of the integral over the unit cube.
eval(HyperRectangleQuadrature.Function, double[], double[]) - Method in class com.imsl.math.HyperRectangleQuadrature
Returns the value of the integral over a cube.
eval(Quadrature.Function, double, double) - Method in class com.imsl.math.Quadrature
Returns the value of the integral from a to b.
eval(double[]) - Method in interface com.imsl.stat.Distribution
Evaluation method to fit the user-supplied probability density function to input data
eval(double[]) - Method in class com.imsl.stat.GammaDistribution
Fits a gamma probability distribution to xData and returns the probability density at each value.
eval(double[], Object[]) - Method in class com.imsl.stat.GammaDistribution
Evaluates a gamma probability distribution with a given set of parameters at each point in xData and returns the probability density at each value.
eval(double, Object[]) - Method in class com.imsl.stat.GammaDistribution
Evaluates a gamma probability density at a given point xData.
eval(double, double) - Method in class com.imsl.stat.InverseCdf
Evaluates the inverse CDF function.
eval(double[]) - Method in class com.imsl.stat.LogNormalDistribution
Fits a lognormal probability distribution to xData and returns the probability density at each value.
eval(double[], Object[]) - Method in class com.imsl.stat.LogNormalDistribution
Evaluates a lognormal probability distribution with a given set of parameters at each point in xData and returns the probability density at each value.
eval(double, Object[]) - Method in class com.imsl.stat.LogNormalDistribution
Evaluates a lognormal probability density function at a given point xData.
eval(double[]) - Method in class com.imsl.stat.NormalDistribution
Fits a normal (Gaussian) probability distribution to xData and returns the probability density at each value.
eval(double[], Object[]) - Method in class com.imsl.stat.NormalDistribution
Evaluates a normal (Gaussian) probability distribution with the given parameters at each point in xData and returns the probability density at each value.
eval(double, Object[]) - Method in class com.imsl.stat.NormalDistribution
Evaluates a normal (Gaussian) probability density at a given point xData.
eval(double[]) - Method in class com.imsl.stat.PoissonDistribution
Fits a Poisson probability distribution to xData and returns the probability density at each value.
eval(double[], Object[]) - Method in class com.imsl.stat.PoissonDistribution
Evaluates a Poisson probability distribution with a given set of parameters at each point in xData and returns the probability density at each value.
eval(double, Object[]) - Method in class com.imsl.stat.PoissonDistribution
Evaluates a Poisson probability density function at a given point xData.
eval(double[], Object[]) - Method in interface com.imsl.stat.ProbabilityDistribution
Evaluates the user-supplied probability density of each value in xData using the supplied probability distribution parameters.
eval(double, Object[]) - Method in interface com.imsl.stat.ProbabilityDistribution
Evaluation method for the user-supplied distribution function and parameters.
evaluateCDF() - Method in class com.imsl.stat.KaplanMeierECDF
Computes the empirical CDF and returns the CDF values up to, but not including the time values returned by getTimes.
evaluateF(int, double[]) - Method in class com.imsl.math.NumericalDerivatives
This method is provided by the user to compute the function values at the current independent variable values y.
evaluateJ(double[]) - Method in class com.imsl.math.NumericalDerivatives
Evaluates the Jacobian for a system of (m) equations in (n) variables.
EWMA - Class in com.imsl.chart.qc
EWMA is an exponentially weighted moving average control chart.
EWMA(AxisXY, double[], double) - Constructor for class com.imsl.chart.qc.EWMA
Creates an exponentially weighted moving average chart.
EWMA(AxisXY, double[], double, double, double) - Constructor for class com.imsl.chart.qc.EWMA
Creates an exponentially weighted moving average chart using the given values for the expected mean and standard deviation.
EXACT_MATCHES - Static variable in class com.imsl.stat.Dissimilarities
Indicates the number of exact matches distance method.
examineStep(int, double, double[]) - Method in class com.imsl.math.ODE
Called before and after each internal step.
excludeFirst(boolean) - Method in class com.imsl.stat.Difference
If set to true, the observations lost due to differencing will be excluded.
exp(Complex) - Static method in class com.imsl.math.Complex
Returns the exponential of a Complex z, exp(z).
exp(double) - Static method in class com.imsl.math.JMath
Returns the exponential of a double.
expectedNormalOrderStatistic(int, int) - Static method in class com.imsl.stat.Ranks
Returns the expected value of a normal order statistic.
expm1(double) - Static method in class com.imsl.math.Hyperbolic
Returns exp(x)-1, the exponential of x minus 1.
exponential(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the exponential cumulative probability distribution function.
exponential(double, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the exponential cumulative probability distribution function.
exponential(double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the exponential probability density function
extrapolate(double) - Method in class com.imsl.math.EpsilonAlgorithm
Extrapolates the convergence limit of a sequence.
extremeValue(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the extreme value cumulative probability distribution function.
extremeValue(double, double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the extreme value cumulative probability distribution function.
extremeValue(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the extreme value probability density function.

F

f(double) - Method in interface com.imsl.chart.ChartFunction
Function to be charted.
f(double) - Method in class com.imsl.chart.ChartSpline
Function to be charted.
f(double, double) - Method in interface com.imsl.chart3d.Surface.ZFunction
Define the surface function.
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockGradObjective
 
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockObjective
 
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective
 
f(double[]) - Method in interface com.imsl.math.HyperRectangleQuadrature.Function
Returns the value of the function at the given point.
f(double[]) - Method in interface com.imsl.math.MinConGenLin.Function
Public interface for the function to be minimized.
f(double[], int, boolean[]) - Method in interface com.imsl.math.MinConNLP.Function
Compute the value of the function at the given point.
f(double) - Method in interface com.imsl.math.MinUncon.Function
Public interface for the smooth function of a single variable to be minimized.
f(double[]) - Method in interface com.imsl.math.MinUnconMultiVar.Function
Public interface for the multivariate function to be minimized.
f(double[], double[]) - Method in interface com.imsl.math.NonlinLeastSquares.Function
Public interface for the nonlinear least-squares function.
f(int, double[]) - Method in interface com.imsl.math.NumericalDerivatives.Function
Returns the equations evaluated at the point y.
f(double, double[]) - Method in interface com.imsl.math.OdeAdamsGear.Function
Computes the value of the function y^{'} = f(t,y) at the given point.
f(double, double[], double[]) - Method in interface com.imsl.math.OdeRungeKutta.Function
Returns the value of the function at the given point.
f(double) - Method in interface com.imsl.math.Quadrature.Function
Returns the value of the function at the given point.
f(double) - Method in interface com.imsl.math.RadialBasis.Function
A radial basis function.
f(double) - Method in class com.imsl.math.RadialBasis.Gaussian
A Gaussian basis function.
f(double) - Method in class com.imsl.math.RadialBasis.HardyMultiquadric
A Hardy multiquadric basis function.
f(double) - Method in interface com.imsl.math.ZerosFunction.Function
Returns the value of the function at the given point.
f(double[], double[]) - Method in interface com.imsl.math.ZeroSystem.Function
Returns the value of the function at the given point.
F(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the F cumulative probability distribution function.
F(double, double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the F cumulative probability distribution function.
f(double[], int, double[], double[], double[]) - Method in interface com.imsl.stat.NonlinearRegression.Function
Computes the weight, frequency, and residual given the parameter vector theta for a single observation.
F(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the F probability density function.
FACE_XA - Static variable in class com.imsl.chart3d.AxisBox
Show the x = a face of the box.
FACE_XB - Static variable in class com.imsl.chart3d.AxisBox
Show the x = b face of the box.
FACE_YA - Static variable in class com.imsl.chart3d.AxisBox
Show the y = a face of the box.
FACE_YB - Static variable in class com.imsl.chart3d.AxisBox
Show the y = b face of the box.
FACE_ZA - Static variable in class com.imsl.chart3d.AxisBox
Show the z = a face of the box.
FACE_ZB - Static variable in class com.imsl.chart3d.AxisBox
Show the z = b face of the box.
fact(int) - Static method in class com.imsl.math.Sfun
Returns the factorial of an integer.
factor - Variable in class com.imsl.math.ComplexLU
This is an n by n Complex matrix containing the LU factorization of the matrix A.
factor - Variable in class com.imsl.math.LU
This is an n by n matrix containing the LU factorization of the matrix A.
FactorAnalysis - Class in com.imsl.stat
Performs Principal Component Analysis or Factor Analysis on a covariance or correlation matrix.
FactorAnalysis(double[][], int, int) - Constructor for class com.imsl.stat.FactorAnalysis
Constructor for FactorAnalysis.
FactorAnalysis.BadVarianceException - Exception in com.imsl.stat
Bad variance error.
FactorAnalysis.BadVarianceException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.BadVarianceException
 
FactorAnalysis.BadVarianceException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.BadVarianceException
 
FactorAnalysis.EigenvalueException - Exception in com.imsl.stat
Eigenvalue error.
FactorAnalysis.EigenvalueException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.EigenvalueException
 
FactorAnalysis.EigenvalueException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.EigenvalueException
 
FactorAnalysis.NonPositiveEigenvalueException - Exception in com.imsl.stat
Non positive eigenvalue error.
FactorAnalysis.NonPositiveEigenvalueException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException
 
FactorAnalysis.NonPositiveEigenvalueException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException
 
FactorAnalysis.NotPositiveSemiDefiniteException - Exception in com.imsl.stat
Covariance matrix not positive semi-definite.
FactorAnalysis.NotPositiveSemiDefiniteException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException
 
FactorAnalysis.NotPositiveSemiDefiniteException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException
 
FactorAnalysis.NotSemiDefiniteException - Exception in com.imsl.stat
Hessian matrix not semi-definite.
FactorAnalysis.NotSemiDefiniteException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.NotSemiDefiniteException
 
FactorAnalysis.NotSemiDefiniteException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.NotSemiDefiniteException
 
FactorAnalysis.RankException - Exception in com.imsl.stat
Rank of covariance matrix error.
FactorAnalysis.RankException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.RankException
 
FactorAnalysis.RankException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.RankException
 
FactorAnalysis.SingularException - Exception in com.imsl.stat
Covariance matrix singular error.
FactorAnalysis.SingularException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.SingularException
 
FactorAnalysis.SingularException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.SingularException
 
factorNumerically() - Method in class com.imsl.math.ComplexSparseCholesky
Computes the numeric factorization of a sparse Hermitian positive definite matrix.
factorNumerically() - Method in class com.imsl.math.SparseCholesky
Computes the numeric factorization of a sparse real symmetric positive definite matrix.
factorSymbolically() - Method in class com.imsl.math.ComplexSparseCholesky
Computes the symbolic factorization of a sparse Hermitian positive definite matrix.
factorSymbolically() - Method in class com.imsl.math.SparseCholesky
Computes the symbolic factorization of a sparse real symmetric positive definite matrix.
fatalError(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML
Receive notification of a non-recoverable error.
FaureSequence - Class in com.imsl.stat
Generates the low-discrepancy Faure sequence.
FaureSequence(int) - Constructor for class com.imsl.stat.FaureSequence
Creates a Faure sequence with the default base.
FaureSequence(int, int, int) - Constructor for class com.imsl.stat.FaureSequence
Creates a Faure sequence.
FeedForwardNetwork - Class in com.imsl.datamining.neural
A representation of a feed forward neural network.
FeedForwardNetwork() - Constructor for class com.imsl.datamining.neural.FeedForwardNetwork
Creates a new instance of FeedForwardNetwork.
FeynmanKac - Class in com.imsl.math
Solves the generalized Feynman-Kac PDE.
FeynmanKac(FeynmanKac.PdeCoefficients) - Constructor for class com.imsl.math.FeynmanKac
Constructs a PDE solver to solve the Feynman-Kac PDE.
FeynmanKac.Boundaries - Interface in com.imsl.math
Public interface for user supplied boundary coefficients and terminal condition the PDE must satisfy.
FeynmanKac.BoundaryInconsistentException - Exception in com.imsl.math
The boundary conditions are inconsistent.
FeynmanKac.BoundaryInconsistentException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.BoundaryInconsistentException
The boundary conditions are inconsistent.
FeynmanKac.ConstraintsInconsistentException - Exception in com.imsl.math
The constraints are inconsistent.
FeynmanKac.ConstraintsInconsistentException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.ConstraintsInconsistentException
The constraints are inconsistent.
FeynmanKac.CorrectorConvergenceException - Exception in com.imsl.math
Corrector failed to converge.
FeynmanKac.CorrectorConvergenceException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.CorrectorConvergenceException
Corrector failed to converge.
FeynmanKac.ErrorTestException - Exception in com.imsl.math
Error test failure detected.
FeynmanKac.ErrorTestException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.ErrorTestException
Error test failure detected.
FeynmanKac.ForcingTerm - Interface in com.imsl.math
Public interface for non-zero forcing term in the Feynman-Kac equation.
FeynmanKac.InitialConstraintsException - Exception in com.imsl.math
The constraints at the initial point are inconsistent.
FeynmanKac.InitialConstraintsException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.InitialConstraintsException
The constraints at the initial point are inconsistent.
FeynmanKac.InitialData - Interface in com.imsl.math
Public interface for adjustment of initial data or as an opportunity for output during the integration steps.
FeynmanKac.IterationMatrixSingularException - Exception in com.imsl.math
Iteration matrix is singular.
FeynmanKac.IterationMatrixSingularException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.IterationMatrixSingularException
Iteration matrix is singular.
FeynmanKac.PdeCoefficients - Interface in com.imsl.math
Public interface for user supplied PDE coefficients in the Feynman-Kac PDE.
FeynmanKac.TcurrentTstopInconsistentException - Exception in com.imsl.math
The end value for the integration in time, tout, is not consistent with the current time value, t.
FeynmanKac.TcurrentTstopInconsistentException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.TcurrentTstopInconsistentException
The end value for the integration in time, tout, is not consistent with the current time value, t.
FeynmanKac.TEqualsToutException - Exception in com.imsl.math
The current integration point in time and the end point are equal.
FeynmanKac.TEqualsToutException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.TEqualsToutException
The current integration point in time and the end point are equal.
FeynmanKac.TimeIntervalTooSmallException - Exception in com.imsl.math
Distance between starting time point and end point for the integration is too small.
FeynmanKac.TimeIntervalTooSmallException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.TimeIntervalTooSmallException
Distance between starting time point and end point for the integration is too small.
FeynmanKac.ToleranceTooSmallException - Exception in com.imsl.math
Tolerance is too small.
FeynmanKac.ToleranceTooSmallException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.ToleranceTooSmallException
Tolerance is too small.
FeynmanKac.TooManyIterationsException - Exception in com.imsl.math
Too many iterations required by the DAE solver.
FeynmanKac.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.math.FeynmanKac.TooManyIterationsException
Too many iterations required by the DAE solver.
FFT - Class in com.imsl.math
FFT functions.
FFT(int) - Constructor for class com.imsl.math.FFT
Constructs an FFT object.
FILL - Static variable in class com.imsl.chart.Draw
 
FILL_FACTOR - Static variable in class com.imsl.math.ComplexSuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
FILL_FACTOR - Static variable in class com.imsl.math.SuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
FILL_TYPE_GRADIENT - Static variable in class com.imsl.chart.ChartNode
Value for attribute "FillType" indicating that the region is to be drawn in a color gradient as specified by the attribute Gradient.
FILL_TYPE_NONE - Static variable in class com.imsl.chart.ChartNode
Value for attribute "FillType" and "FillOutlineType" indicating that the region is not to be drawn.
FILL_TYPE_PAINT - Static variable in class com.imsl.chart.ChartNode
Value for attribute "FillType" indicating that the region is to be drawn using the texture specified by the attribute FillPaint.
FILL_TYPE_SOLID - Static variable in class com.imsl.chart.ChartNode
Value for attribute "FillType" and "FillOutlineType" indicating that the region is to be drawn using the solid color specified by the attribute FillColor or FillOutlineColor.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.Draw
Fills a circular or elliptical arc covering the specified rectangle.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawMap
Fills a circular or elliptical arc covering the specified rectangle.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawPick
Fills a circular or elliptical arc covering the specified rectangle.
fillColor - Variable in class com.imsl.chart.Draw
 
fillOutlineColor - Variable in class com.imsl.chart.Draw
 
fillOutlineType - Variable in class com.imsl.chart.Draw
 
fillPaint - Variable in class com.imsl.chart.Draw
 
FillPaint - Class in com.imsl.chart
A collection of methods to create Paint objects for fill areas.
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.Draw
Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.Draw
Fill a polygon defined by a Polygon object.
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.DrawMap
Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.DrawMap
Fill a polygon defined by a Polygon object.
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.DrawPick
Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.DrawPick
Fill a polygon defined by a Polygon object.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.Draw
Fill a rectangle.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.DrawMap
Fill a rectangle.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.DrawPick
Fill a rectangle.
fillType - Variable in class com.imsl.chart.Draw
 
filter() - Method in class com.imsl.stat.KalmanFilter
Performs Kalman filtering and evaluates the likelihood function for the state-space model.
finalize() - Method in class com.imsl.chart.Chart
 
finalize() - Method in class com.imsl.chart3d.Chart3D
 
Finance - Class in com.imsl.finance
Collection of finance functions.
findColumn(String) - Method in class com.imsl.io.AbstractFlatFile
Maps the given ResultSet column name to its ResultSet column index.
findColumnName(int) - Method in class com.imsl.io.AbstractFlatFile
Maps the given columnIndex into its column name.
findLink(Node, Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the Link between two Nodes.
findLinks(Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns all of the Links to a given Node.
finite(double) - Static method in class com.imsl.math.IEEE
Finite number test on an argument of type double.
fire() - Method in class com.imsl.chart.DrawPick
Fires the pickListeners for all of the picked nodes.
firePickListeners(MouseEvent) - Method in class com.imsl.chart.ChartNode
Fires the pick listeners defined at this node and at all of its ancestors, if the event "hits" the node.
first() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the first row in this ResultSet object.
FIRST_DERIVATIVE - Static variable in class com.imsl.math.CsInterpolate
 
FIRST_GRAM_SCHMIDT - Static variable in class com.imsl.math.GenMinRes
Indicates the first Gram-Schmidt implementation method is to be used.
FIRST_HOUSEHOLDER - Static variable in class com.imsl.math.GenMinRes
Indicates the first Householder implementation method is to be used.
FlatFile - Class in com.imsl.io
Reads a text file as a ResultSet.
FlatFile(BufferedReader, Tokenizer) - Constructor for class com.imsl.io.FlatFile
Creates a FlatFile from a BufferedReader.
FlatFile(BufferedReader) - Constructor for class com.imsl.io.FlatFile
Creates a FlatFile with the CSV tokenizer.
FlatFile(String) - Constructor for class com.imsl.io.FlatFile
Creates a FlatFile from a CSV file.
FlatFile(String, Tokenizer) - Constructor for class com.imsl.io.FlatFile
Creates a FlatFile from a file with the default tokenizer.
FlatFile.Parser - Interface in com.imsl.io
Defines a method that parses a String into an Object.
floatValue() - Method in class com.imsl.math.Complex
Returns the value of the real part as a float.
floatValue() - Method in class com.imsl.math.Physical
Returns the value of this dimensionless object.
floor(double) - Static method in class com.imsl.math.JMath
Returns the value of a double rounded toward negative infinity to an integral value.
force(int, double[], double, double, double[], double[], double[][], double[], double[][]) - Method in interface com.imsl.math.FeynmanKac.ForcingTerm
Computes approximations to the forcing term phi(f,x,t) and its derivative partial phi/partial y.
forecast(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Computes a forecast using the Network.
forecast(double[]) - Method in class com.imsl.datamining.neural.Network
Returns a forecast for each of the Network's outputs computed from the trained Network.
forecast(int) - Method in class com.imsl.stat.ARAutoUnivariate
Returns forecasts and associated confidence interval offsets.
forecast(int) - Method in class com.imsl.stat.ARMA
Computes forecasts and their associated probability limits for an ARMA model.
forecast(int) - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns forecasts for lead times l=1,2,ldots,rm{nForecast} at origins z.length-backwardOrigin-1+j where j=1,ldots,rm{backwardOrigin}+1.
forecast(int) - Method in class com.imsl.stat.AutoARIMA
Computes forecasts, associated probability limits and psi weights for the given outlier contaminated time series.
format(LogRecord) - Method in class com.imsl.IMSLFormatter
Format the given log record and return the formatted string.
format(int, Object, int, int, ParsePosition) - Method in class com.imsl.math.PrintMatrixFormat
Returns a formatted string.
formatLabel(double, double) - Method in class com.imsl.chart.Data
 
formatMessage(String, String, Object[]) - Static method in class com.imsl.Messages
A message is formatted using a MessageFormat string retrieved from the named resource bundle using the given key.
formatMessage(String, String) - Static method in class com.imsl.Messages
A message is formatted, without arguments, using a MessageFormat string retrieved from the named resource bundle using the given key.
forward(Complex[]) - Method in class com.imsl.math.ComplexFFT
Compute the Fourier coefficients of a complex periodic sequence.
forward(double[]) - Method in class com.imsl.math.FFT
Compute the Fourier coefficients of a real periodic sequence.
FORWARD_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression
Indicates forward regression.
frobeniusNorm(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Return the Frobenius norm of a Complex matrix.
frobeniusNorm() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the Frobenius norm of the matrix.
frobeniusNorm(double[][]) - Static method in class com.imsl.math.Matrix
Return the Frobenius norm of a matrix.
frobeniusNorm() - Method in class com.imsl.math.SparseMatrix
Returns the Frobenius norm of the matrix.
FULL - Static variable in class com.imsl.math.PrintMatrix
This flag as the argument to setMatrixType, indicates that the full matrix is to be printed.
fv(double, int, double, double, int) - Static method in class com.imsl.finance.Finance
Returns the future value of an investment.
fvschedule(double, double[]) - Static method in class com.imsl.finance.Finance
Returns the future value of an initial principal taking into consideration a schedule of compound interest rates.

G

g(double) - Method in interface com.imsl.datamining.neural.Activation
Returns the value of the activation function.
g(double) - Method in interface com.imsl.math.MinUncon.Derivative
Public interface for the smooth function of a single variable to be minimized.
g(double) - Method in interface com.imsl.math.RadialBasis.Function
The derivative of the radial basis function used to calculate the gradient of the radial basis approximation.
g(double) - Method in class com.imsl.math.RadialBasis.Gaussian
The derivative of the Gaussian basis function used to calculate the gradient of the radial basis approximation.
g(double) - Method in class com.imsl.math.RadialBasis.HardyMultiquadric
The derivative of the Hardy multiquadric basis function used to calculate the gradient of the radial basis approximation.
gamma(double) - Static method in class com.imsl.math.Sfun
Returns the Gamma function of a double.
gamma(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the gamma cumulative probability distribution function.
gamma(double, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the gamma cumulative probability distribution function.
gamma(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the gamma probability density function.
GammaDistribution - Class in com.imsl.stat
Evaluates a gamma probability density for a given set of data.
GammaDistribution() - Constructor for class com.imsl.stat.GammaDistribution
 
gammaIncomplete(double, double) - Static method in class com.imsl.math.Sfun
Evaluates the incomplete gamma function.
GARCH - Class in com.imsl.stat
Computes estimates of the parameters of a GARCH(p,q) model.
GARCH(int, int, double[], double[]) - Constructor for class com.imsl.stat.GARCH
Constructor for GARCH.
GARCH.ConstrInconsistentException - Exception in com.imsl.stat
The equality constraints are inconsistent.
GARCH.ConstrInconsistentException(String) - Constructor for exception com.imsl.stat.GARCH.ConstrInconsistentException
 
GARCH.ConstrInconsistentException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.ConstrInconsistentException
 
GARCH.EqConstrInconsistentException - Exception in com.imsl.stat
The equality constraints and the bounds on the variables are found to be inconsistent.
GARCH.EqConstrInconsistentException(String) - Constructor for exception com.imsl.stat.GARCH.EqConstrInconsistentException
 
GARCH.EqConstrInconsistentException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.EqConstrInconsistentException
 
GARCH.NoVectorXException - Exception in com.imsl.stat
No vector X satisfies all of the constraints.
GARCH.NoVectorXException(String) - Constructor for exception com.imsl.stat.GARCH.NoVectorXException
 
GARCH.NoVectorXException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.NoVectorXException
 
GARCH.TooManyIterationsException - Exception in com.imsl.stat
Number of function evaluations exceeded 1000.
GARCH.TooManyIterationsException(String) - Constructor for exception com.imsl.stat.GARCH.TooManyIterationsException
 
GARCH.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.TooManyIterationsException
 
GARCH.VarsDeterminedException - Exception in com.imsl.stat
The variables are determined by the equality constraints.
GARCH.VarsDeterminedException(String) - Constructor for exception com.imsl.stat.GARCH.VarsDeterminedException
 
GARCH.VarsDeterminedException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.VarsDeterminedException
 
GENERALIZED_LEAST_SQUARES - Static variable in class com.imsl.stat.FactorAnalysis
Indicates generalized least squares method.
GenMinRes - Class in com.imsl.math
Linear system solver using the restarted Generalized Minimum Residual (GMRES) method.
GenMinRes(int, GenMinRes.Function) - Constructor for class com.imsl.math.GenMinRes
GMRES linear system solver constructor.
GenMinRes.Function - Interface in com.imsl.math
Public interface for the user supplied function to GenMinRes.
GenMinRes.Norm - Interface in com.imsl.math
Public interface for the user supplied function to the GenMinRes object used for the norm Vert X Vert when the Gram-Schmidt implementation is used.
GenMinRes.Preconditioner - Interface in com.imsl.math
Public interface for the user supplied function to GenMinRes used for preconditioning.
GenMinRes.TooManyIterationsException - Exception in com.imsl.math
Maximum number of iterations exceeded.
GenMinRes.TooManyIterationsException(String) - Constructor for exception com.imsl.math.GenMinRes.TooManyIterationsException
 
GenMinRes.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.math.GenMinRes.TooManyIterationsException
 
GenMinRes.VectorProducts - Interface in com.imsl.math
Public interface for the user supplied function to the GenMinRes object used for the inner product when the Gram-Schmidt implementation is used.
geometric(int, double) - Static method in class com.imsl.stat.Cdf
Evaluates the discrete geometric cumulative probability distribution function.
geometric(double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the discrete geometric cumulative probability distribution function.
geometric(int, double) - Static method in class com.imsl.stat.Pdf
Evaluates the discrete geometric probability density function.
get(String) - Method in class com.imsl.chart.xml.ChartXML
Returns a generated object given the id attribute in the XML tag that created the object.
get(int, int) - Method in class com.imsl.math.ComplexSparseMatrix
Returns the value of an element in the matrix.
get(int, int) - Method in class com.imsl.math.SparseMatrix
Returns the value of an element in the matrix.
getAbsoluteErrorTolerances() - Method in class com.imsl.math.FeynmanKac
Returns absolute error tolerances.
getAbsoluteH() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the value for H used for setting limits.
getAbstractParent() - Method in class com.imsl.chart.AbstractChartNode
Returns the parent of this node.
getActivation() - Method in class com.imsl.datamining.neural.Perceptron
Returns the activation function.
getAdjustedANOVA() - Method in class com.imsl.stat.ANCOVA
Returns the partial sum of squares for the one-way analysis of covariance.
getAdjustedRSquared() - Method in class com.imsl.stat.ANOVA
Returns the adjusted R-squared (in percent).
getAIC() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final estimate for Akaike's Information Criterion (AIC) at the optimum.
getAIC() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns Akaike's information criterion (AIC).
getAIC() - Method in class com.imsl.stat.ARSeasonalFit
Returns the final estimate for Akaike's Information Criterion (AIC) at the optimum.
getAIC() - Method in class com.imsl.stat.AutoARIMA
Returns Akaike's information criterion (AIC) for the optimum model.
getAICC() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns Akaike's Corrected Information Criterion (AICC).
getAICC() - Method in class com.imsl.stat.AutoARIMA
Returns Akaike's Corrected Information Criterion (AICC) for the optimum model.
getAkaike() - Method in class com.imsl.stat.GARCH
Returns the value of Akaike Information Criterion evaluated at the estimated parameter array.
getAlignment() - Method in class com.imsl.chart.Text
Gets the alignment for this Text object.
getALT() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ALT" attribute.
getALT() - Method in class com.imsl.chart.DrawMap
Returns the current ALT string.
getANCOVA() - Method in class com.imsl.stat.ANCOVA
Returns an array containing the one-way analysis of covariance assuming parallelism.
getANOVA() - Method in class com.imsl.math.RadialBasis
Returns the ANOVA statistics from the linear regression.
getANOVA() - Method in class com.imsl.stat.LinearRegression
Get an analysis of variance table and related statistics.
getANOVA() - Method in class com.imsl.stat.StepwiseRegression
Get an analysis of variance table and related statistics.
getANOVA() - Method in class com.imsl.stat.UserBasisRegression
Get an analysis of variance table and related statistics.
getANOVATable() - Method in class com.imsl.stat.ANOVAFactorial
Returns the analysis of variance table.
getANOVATables() - Method in class com.imsl.stat.ANCOVA
Returns a matrix of size ngroup by 15 containing the analysis of variance tables for each linear regression model fitted separately to each treatment group.
getAR() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final auto regressive parameter estimates at the optimum AIC using the estimation method specified in setEstimationMethod .
getAR() - Method in class com.imsl.stat.ARMA
Returns the final autoregressive parameter estimates.
getAR() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the final autoregressive parameter estimates.
getAR() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the final autoregressive parameter estimates.
getAR() - Method in class com.imsl.stat.ARSeasonalFit
Returns the final autoregressive parameter estimates at the optimum in the transformed series W_t.
getAR() - Method in class com.imsl.stat.AutoARIMA
Returns the final autoregressive parameter estimates of the optimum model.
getAR() - Method in class com.imsl.stat.GARCH
Returns the estimated values of autoregressive (AR) parameters.
getAROrder() - Method in class com.imsl.stat.ARSeasonalFit
Returns optimum number of lags, p, for the optimum autoregressive AR(p) model.
getArray(int) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as an Array object in the Java programming language.
getArray(String) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as an Array object in the Java programming language.
getArray() - Method in class com.imsl.stat.ANOVA
Returns the ANOVA values as an array.
getAsciiStream(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a stream of ASCII characters.
getAsciiStream(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a stream of ASCII characters.
getAttribute(String) - Method in class com.imsl.chart.AbstractChartNode
Gets an attribute.
getAutoCorrelations() - Method in class com.imsl.stat.AutoCorrelation
Returns the autocorrelations of the time series x.
getAutoCorrelationX() - Method in class com.imsl.stat.CrossCorrelation
Returns the autocorrelations of the time series x.
getAutoCorrelationY() - Method in class com.imsl.stat.CrossCorrelation
Returns the autocorrelations of the time series y.
getAutoCovariance() - Method in class com.imsl.stat.ARMA
Returns the autocovariances of the time series z.
getAutoCovariances() - Method in class com.imsl.stat.AutoCorrelation
Returns the variance and autocovariances of the time series x.
getAutoCovarianceX() - Method in class com.imsl.stat.CrossCorrelation
Returns the autocovariances of the time series x.
getAutoCovarianceY() - Method in class com.imsl.stat.CrossCorrelation
Returns the autocovariances of the time series y.
getAutoscaleInput() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "AutoscaleInput" attribute.
getAutoscaleMinimumTimeInterval() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "AutoscaleMinimumTimeInterval" attribute.
getAutoscaleOutput() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "AutoscaleOutput" attribute.
getAxis() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Axis" attribute.
getAxisBox() - Method in class com.imsl.chart3d.AxisXYZ
Return the axis box node.
getAxisLabel() - Method in class com.imsl.chart.Axis1D
Returns the label node associated with this axis.
getAxisLabel() - Method in class com.imsl.chart3d.Axis3D
Returns the label node associated with this axis.
getAxisLine() - Method in class com.imsl.chart.Axis1D
Returns the axis line node associated with this axis.
getAxisLine() - Method in class com.imsl.chart3d.Axis3D
Returns the axis line node associated with this axis.
getAxisR() - Method in class com.imsl.chart.Polar
Return the radius axis node.
getAxisRLabel() - Method in class com.imsl.chart.AxisR
Returns the AxisRLabel node.
getAxisRLine() - Method in class com.imsl.chart.AxisR
Returns the AxisRLine node.
getAxisRMajorTick() - Method in class com.imsl.chart.AxisR
Returns the major tick node associated with this axis.
getAxisTheta() - Method in class com.imsl.chart.Polar
Return the angular axis node.
getAxisTitle() - Method in class com.imsl.chart.Axis1D
Returns the title node associated with this axis.
getAxisTitle() - Method in class com.imsl.chart3d.Axis3D
Returns the title node associated with this axis.
getAxisTitlePosition() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "AxisTitlePosition" attribute.
getAxisUnit() - Method in class com.imsl.chart.Axis1D
Returns the unit node associated with this axis.
getAxisX() - Method in class com.imsl.chart.AxisXY
Return the x-axis node.
getAxisX() - Method in class com.imsl.chart3d.AxisXYZ
Return the x-axis node.
getAxisY() - Method in class com.imsl.chart.AxisXY
Return the y-axis node.
getAxisY() - Method in class com.imsl.chart3d.AxisXYZ
Return the y-axis node.
getAxisZ() - Method in class com.imsl.chart3d.AxisXYZ
Return the z-axis node.
getBackground() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Background" attribute.
getBackground() - Method in class com.imsl.chart3d.Chart3D
Returns the value of the "Background" attribute.
getBackwardOrigin() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the maximum backward origin.
getBackwardOrigin() - Method in class com.imsl.stat.ARMA
Returns the user-specified backward origin
getBackwardOrigin() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the current value for forecasting backward origin.
getBalancedTable() - Method in class com.imsl.stat.TableMultiWay
Returns an object containing the balanced table.
getBarData() - Method in class com.imsl.chart.Bar
Returns the "BarData" attribute.
getBarGap() - Method in class com.imsl.chart.ChartNode
Returns the value of the "BarGap" attribute.
getBarItem() - Method in class com.imsl.chart.BarSet
Returns an array of BarItems.
getBarItem(int) - Method in class com.imsl.chart.BarSet
Returns the BarItem given the index.
getBarMinus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the value of the attribute "BarMinus" containing the C^{-} bars.
getBarPlus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the value of the attribute "BarPlus" containing the C^{+} bars.
getBarSet() - Method in class com.imsl.chart.Bar
Returns the BarSet object.
getBarSet(int, int) - Method in class com.imsl.chart.Bar
Returns the BarSet object.
getBarSet(int) - Method in class com.imsl.chart.Bar
Returns the BarSet object.
getBarType() - Method in class com.imsl.chart.ChartNode
Returns the value of the "BarType" attribute.
getBarWidth() - Method in class com.imsl.chart.ChartNode
Returns the value of the "BarWidth" attribute.
getBase() - Method in class com.imsl.stat.FaureSequence
Returns the base.
getBias() - Method in class com.imsl.datamining.neural.Perceptron
Returns the bias for this Perceptron.
getBIC() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the Bayesian Information Criterion (BIC).
getBIC() - Method in class com.imsl.stat.AutoARIMA
Returns the Bayesian Information Criterion (BIC) for the optimum model.
getBigDecimal(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.math.BigDecimal with full precision.
getBigDecimal(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.math.BigDecimal with full precision.
getBinaryStream(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a binary stream of uninterpreted bytes.
getBinaryStream(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a stream of uninterpreted bytes.
getBlob(int) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Blob object in the Java programming language.
getBlob(String) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Blob object in the Java programming language.
getBlomScores(double[]) - Method in class com.imsl.stat.Ranks
Gets the Blom version of normal scores for each observation.
getBodies() - Method in class com.imsl.chart.BoxPlot
Returns a node containing the body elements in the Box plot.
getBoolean(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a boolean in the Java programming language.
getBoolean(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a boolean in the Java programming language.
getBooleanAttribute(String, boolean) - Method in class com.imsl.chart.AbstractChartNode
Convenience routine to get a Boolean-valued attribute.
getBoundingSphere() - Method in class com.imsl.chart3d.ChartNode3D
Gets the spherical bounding region object BoundingSphere.
getBounds() - Method in class com.imsl.datamining.neural.ScaleFilter
Retrieves bounds used during bounded scaling.
getBoxPlotType() - Method in class com.imsl.chart.BoxPlot
Returns the value of the "BoxPlotType" attribute.
getBreakpoints() - Method in class com.imsl.math.Spline
Returns a copy of the breakpoints.
getByte(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a byte in the Java programming language.
getByte(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a byte in the Java programming language.
getBytes(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a byte array in the Java programming language.
getBytes(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a byte array in the Java programming language.
getCanvas() - Method in class com.imsl.chart3d.Chart3D
 
getCanvas() - Method in class com.imsl.chart3d.JFrameChart3D
Returns the Canvas3DChart into which the chart is drawn.
getCaseAnalysis() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the case analysis.
getCaseStatistics(double[], double) - Method in class com.imsl.stat.LinearRegression
Returns the case statistics for an observation.
getCaseStatistics(double[], double, double) - Method in class com.imsl.stat.LinearRegression
Returns the case statistics for an observation and a weight.
getCaseStatistics(double[], double, int) - Method in class com.imsl.stat.LinearRegression
Returns the case statistics for an observation and future response count for the desired prediction interval.
getCaseStatistics(double[], double, double, int) - Method in class com.imsl.stat.LinearRegression
Returns the case statistics for an observation, weight, and future response count for the desired prediction interval.
getCaseStatistics() - Method in class com.imsl.stat.ProportionalHazards
Returns the case statistics for each observation.
getCellCounts() - Method in class com.imsl.stat.ChiSquaredTest
Returns the cell counts.
getCensorColumn() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the column index of x containing the optional censoring code for each observation.
getCensorColumn() - Method in class com.imsl.stat.ProportionalHazards
Returns the column index of x containing the optional censoring code for each observation.
getCenter() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the value of the attribute "Center".
getCenter() - Method in class com.imsl.datamining.neural.ScaleFilter
Retrieves the measure of center to be used during z-score scaling.
getCenter() - Method in class com.imsl.stat.ARSeasonalFit
Returns the current setting for centering the input time series.
getCenterLine() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the center line.
getCharacterStream(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.
getCharacterStream(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.
getChart() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Chart" attribute.
getChart(HttpServletRequest) - Method in class com.imsl.chart.ChartServlet
Returns the chart found in the session saved with the key "chart"+id, where id is the value of the "id" parameter in the request.
getChart() - Method in class com.imsl.chart.JFrameChart
Return the Chart object.
getChart() - Method in class com.imsl.chart.JPanelChart
Return the Chart object.
getChart() - Method in class com.imsl.chart.xml.ChartXML
Returns the root node of the chart tree.
getChart3D() - Method in class com.imsl.chart3d.Canvas3DChart
Returns the Chart3D associated with this canvas.
getChart3D() - Method in class com.imsl.chart3d.JFrameChart3D
Return the Chart object.
getChartServletName() - Method in class com.imsl.chart.JspBean
Returns the URL of the servlet used to render the chart.
getChartTitle() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ChartTitle" attribute.
getChildList() - Method in class com.imsl.chart.AbstractChartNode
Returns the children of this node.
getChildren() - Method in class com.imsl.chart.ChartNode
Returns an array of the children of this node.
getChildren() - Method in class com.imsl.chart3d.ChartNode3D
Returns an array of the children of this node.
getChiSquared() - Method in class com.imsl.stat.ChiSquaredTest
Returns the chi-squared statistic.
getChiSquared() - Method in class com.imsl.stat.ContingencyTable
Returns the Pearson chi-squared test statistic.
getChiSquared() - Method in class com.imsl.stat.NormalityTest
Returns the chi-square statistic for the chi-squared goodness-of-fit test.
getChiSquaredTest() - Method in class com.imsl.stat.NormOneSample
Returns the test statistic associated with the chi-squared test for variances.
getChiSquaredTest() - Method in class com.imsl.stat.NormTwoSample
Returns the test statistic associated with the chi-squared test for common, or pooled, variances.
getChiSquaredTestDF() - Method in class com.imsl.stat.NormOneSample
Returns the degrees of freedom associated with the chi-squared test for variances.
getChiSquaredTestDF() - Method in class com.imsl.stat.NormTwoSample
Returns the degrees of freedom associated with the chi-squared test for the common, or pooled, variances.
getChiSquaredTestP() - Method in class com.imsl.stat.NormOneSample
Returns the probability of a larger chi-squared associated with the chi-squared test for variances.
getChiSquaredTestP() - Method in class com.imsl.stat.NormTwoSample
Returns the probability of a larger chi-squared associated with the chi-squared test for common, or pooled, variances.
getClassCounts(int[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns the number of patterns for each target classification.
getClassificationErrors() - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns the classification probability errors for each pattern in the training data.
getClassificationVariableCounts() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the number of values taken by each classification variable.
getClassificationVariableValues() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the distinct values of the classification variables in ascending order.
getClassMembership() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the group number to which the observation was classified.
getClassTable() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the classification table.
getClassValueCounts() - Method in class com.imsl.stat.ProportionalHazards
Returns the number of values taken by each classification variable.
getClassValues() - Method in class com.imsl.stat.ProportionalHazards
Returns the class values taken by each classification variable.
getClipBounds() - Method in class com.imsl.chart.Draw
Get the clipping rectangle.
getClipData() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ClipData" attribute.
getClob(int) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Clob object in the Java programming language.
getClob(String) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Clob object in the Java programming language.
getClose() - Method in class com.imsl.chart.HighLowClose
Gets the value of the attribute "Close".
getClusterCounts() - Method in class com.imsl.stat.ClusterKMeans
Returns the number of observations in each cluster.
getClusterLeftSons() - Method in class com.imsl.stat.ClusterHierarchical
Returns the left sons of each merged cluster.
getClusterLevel() - Method in class com.imsl.stat.ClusterHierarchical
Returns the level at which the clusters are joined.
getClusterMembership(int) - Method in class com.imsl.stat.ClusterHierarchical
Returns the cluster membership of each observation.
getClusterMembership() - Method in class com.imsl.stat.ClusterKMeans
Returns the cluster membership for each observation.
getClusterRightSons() - Method in class com.imsl.stat.ClusterHierarchical
Returns the right sons of each merged cluster.
getClusterSSQ() - Method in class com.imsl.stat.ClusterKMeans
Returns the within sum of squares for each cluster.
getCMinus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the C^{-} values.
getCoefficient(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests
Returns the estimate for a coefficient.
getCoefficient(int) - Method in class com.imsl.stat.NonlinearRegression
Returns the estimate for a coefficient.
getCoefficient(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests
Returns the estimate for a coefficient of the independent variable.
getCoefficientOfVariation() - Method in class com.imsl.stat.ANOVA
Returns the coefficient of variation (in percent).
getCoefficients() - Method in class com.imsl.io.MPSReader.Row
Returns the coeffients of this row as a dense array.
getCoefficients() - Method in class com.imsl.math.Spline2D
Returns the coefficients for the tensor-product spline.
getCoefficients() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the linear discriminant function coefficients.
getCoefficients() - Method in class com.imsl.stat.LinearRegression
Returns the regression coefficients.
getCoefficients() - Method in class com.imsl.stat.NonlinearRegression
Returns the regression coefficients.
getCoefficients() - Method in class com.imsl.stat.UserBasisRegression
Returns the regression coefficients.
getCoefficientStatistics(int) - Method in class com.imsl.stat.SelectionRegression.Statistics
Returns the coefficients statistics for each of the best regressions found for each subset considered.
getCoefficientTable(int) - Method in class com.imsl.stat.ANCOVA
Returns a matrix of size ncov + 1 by 4 containing statistics for a linear regression model fitted separately for each of the ngroup treatment groups.
getCoefficientTables() - Method in class com.imsl.stat.ANCOVA
Returns an array containing statistics for a linear regression model fitted separately for all ngroup treatments.
getCoefficientTTests() - Method in class com.imsl.stat.LinearRegression
Returns statistics relating to the regression coefficients.
getCoefficientTTests() - Method in class com.imsl.stat.StepwiseRegression
Returns the student-t test statistics for the regression coefficients.
getCoefficientVIF() - Method in class com.imsl.stat.StepwiseRegression
Returns the variance inflation factors for the final model in this invocation.
getColorAttribute(String) - Method in class com.imsl.chart.AbstractChartNode
Convenience routine to get a Color-valued attribute.
getColorFunction() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "ColorFunction" attribute.
getColormap() - Method in class com.imsl.chart.Heatmap
Returns the value of the "Colormap" attribute.
getColormap() - Method in class com.imsl.chart.Treemap
Returns the value of the "Colormap" attribute.
getColumn() - Method in class com.imsl.io.MPSReader.Element
Returns the column index.
getColumnClass(int) - Method in class com.imsl.io.AbstractFlatFile
Returns the class of the items in the specified column.
getColumnCount() - Method in class com.imsl.io.AbstractFlatFile
Returns the number of columns in this ResultSet object.
getColumnCount() - Method in class com.imsl.io.FlatFile
Returns the number of columns in this ResultSet object.
getColumnPermutationMethod() - Method in class com.imsl.math.ComplexSuperLU
Returns the method that will be used to permute the columns of the input matrix.
getColumnPermutationMethod() - Method in class com.imsl.math.SuperLU
Returns the method that will be used to permute the columns of the input matrix.
getCompleteTimes() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns an int array of all time points, including values for times with missing values in z.
getCompleteTimes() - Method in class com.imsl.stat.AutoARIMA
Returns all time points at which the original series was observed, including values for times with missing values in x.
getCompleteTimeSeries() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns a double precision vector of length tpoints[tpoints.length-1]-tpoints[0]+1 containing the observed values in the time series z plus estimates for missing values in gaps identified in tpoints.
getCompleteTimeSeries() - Method in class com.imsl.stat.AutoARIMA
Returns the original series with potentially missing values replaced by estimates.
getComponent() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Component" attribute.
getConcatenatedViewport() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Viewport" attribute concatenated with the "Viewport" attributes set in its ancestor nodes.
getConcatenatedViewport() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Viewport" attribute concatenated with the "Viewport" attributes set in its ancestor nodes.
getConcurrency() - Method in class com.imsl.io.AbstractFlatFile
Returns the concurrency mode of this ResultSet object.
getConditionNumber() - Method in class com.imsl.math.ComplexSuperLU
Returns the estimate of the reciprocal condition number of the matrix A.
getConditionNumber() - Method in class com.imsl.math.SuperLU
Returns the estimate of the reciprocal condition number of the matrix A.
getConfidence() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the confidence level for calculating confidence limit deviations returned from getDeviations.
getConfidence() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the confidence level used for calculating deviations in getDeviations.
getConfidenceInterval(double, int, int, int) - Method in class com.imsl.stat.ANOVA
Computes the confidence interval associated with the difference of means between two groups using a specified method.
getConfidenceInterval() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Confidence Interval on the mean for an observation.
getConstant() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the estimate for the constant parameter in the ARMA series.
getConstant() - Method in class com.imsl.stat.ARMA
Returns the constant parameter estimate.
getConstant() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the estimate for the constant parameter in the ARMA series.
getConstant() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the constant parameter estimate.
getConstant() - Method in class com.imsl.stat.AutoARIMA
Returns the constant parameter estimate for the optimum model.
getConstantColumn() - Method in class com.imsl.stat.ProportionalHazards
Returns the column index of x containing the constant to be added to the linear response.
getConstraintResiduals() - Method in class com.imsl.math.MinConNLP
Returns the constraint residuals.
getContingencyCoef() - Method in class com.imsl.stat.ContingencyTable
Returns contingency coefficient.
getContourLegend() - Method in class com.imsl.chart.Contour
Returns the contour chart legend.
getContourLevel() - Method in class com.imsl.chart.Contour
Returns all of the contour levels.
getContourLevel(int) - Method in class com.imsl.chart.Contour
Returns a ContourLevel.
getContributions() - Method in class com.imsl.stat.ContingencyTable
Returns the contributions to chi-squared for each cell in the table.
getControlData() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the Data object for the control data.
getControlLimit() - Method in class com.imsl.chart.qc.ControlLimit
Returns the value of the attribute "ControlLimit".
getConvergenceTol() - Method in class com.imsl.stat.ProportionalHazards
Returns the convergence tolerance used.
getConvergenceTolerance() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the tolerance level used to determine convergence of the nonlinearleast-squares and maximum likelihood algorithms.
getConvergenceTolerance() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the current value of convergence tolerance used by the AR_1 and AR_P estimation methods.
getCooksDistance() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns Cook's Distance for an observation.
getCoordinates() - Method in class com.imsl.chart.Dendrogram
Convenience routine to get the "Coordinates" attribute.
getCorrelations() - Method in class com.imsl.stat.FactorAnalysis
Returns the correlations of the principal components.
getCount() - Method in class com.imsl.stat.FaureSequence
 
getCovariance() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the array of covariances.
getCovarianceMatrix() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the estimated asymptotic covariance matrix of the coefficients.
getCovariancesSwept() - Method in class com.imsl.stat.StepwiseRegression
Returns the results after cov has been swept for the columns corresponding to the variables in the model.
getCovB() - Method in class com.imsl.stat.KalmanFilter
Returns the mean squared error matrix for b divided by sigma squared.
getCovV() - Method in class com.imsl.stat.KalmanFilter
Returns the variance-covariance matrix of v divided by sigma squared.
getCPlus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the C^{+} values.
getCramersV() - Method in class com.imsl.stat.ContingencyTable
Returns Cramer's V.
getCreateImageMap() - Method in class com.imsl.chart.JspBean
Returns true if a client-side imagemap is to be created.
getCriterionOption() - Method in class com.imsl.stat.SelectionRegression
Returns the criterion option used to calculate the regression estimates.
getCriterionValues(int) - Method in class com.imsl.stat.SelectionRegression.Statistics
Returns an array containing the values of the best criterion for the number of variables considered.
getCross() - Method in class com.imsl.chart.AxisXY
Returns the value of the "Cross" attribute.
getCrossCorrelation() - Method in class com.imsl.stat.CrossCorrelation
Returns the cross-correlations between the time series x and y.
getCrossCorrelation() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the cross-correlations between the channels of x and y.
getCrossCovariance() - Method in class com.imsl.stat.CrossCorrelation
Returns the cross-covariances between the time series x and y.
getCrossCovariance() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the cross-covariances between the channels of x and y.
getCumulativeAxis() - Method in class com.imsl.chart.qc.ParetoChart
Returns the "CumulativeAxis" attribute.
getCumulativeLine() - Method in class com.imsl.chart.qc.ParetoChart
Returns the "CumulativeLine" attribute.
getCursorName() - Method in class com.imsl.io.AbstractFlatFile
Gets the name of the SQL cursor used by this ResultSet object.
getCustomMarkerFactory() - Method in class com.imsl.chart3d.Data
Returns a custom marker factory.
getCustomTransform() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "CustomTransform" attribute.
getCutpoints() - Method in class com.imsl.stat.ChiSquaredTest
Returns the cutpoints.
getDataMarkers() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the "DataMarkers" attribute containing the data markers.
getDataMarkersAxis() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the "DataMarkersAxis" attribute containing the axis associated with the data markers.
getDataType() - Method in class com.imsl.chart.ChartNode
Returns the value of the "DataType" attribute.
getDataType() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "DataType" attribute.
getDate(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDaysInYear(GregorianCalendar) - Method in interface com.imsl.finance.BasisPart
Returns the number of days in the year.
getDegreesOfFreedom() - Method in class com.imsl.stat.ChiSquaredTest
Returns the degrees of freedom in chi-squared.
getDegreesOfFreedom() - Method in class com.imsl.stat.ContingencyTable
Returns the degrees of freedom for the chi-squared tests associated with the table.
getDegreesOfFreedom() - Method in class com.imsl.stat.NormalityTest
Returns the degrees of freedom for the chi-squared goodness-of-fit test.
getDegreesOfFreedomForError() - Method in class com.imsl.stat.ANOVA
Returns the degrees of freedom for error.
getDegreesOfFreedomForModel() - Method in class com.imsl.stat.ANOVA
Returns the degrees of freedom for model.
getDensity() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Density" attribute.
getDesignVariableMeans() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the means of the design variables.
getDeviations() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the deviations used for calculating the forecast confidence limits.
getDeviations() - Method in class com.imsl.stat.ARMA
Returns the deviations used for calculating the forecast confidence limits.
getDeviations() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the deviations from each forecast used for calculating the forecast confidence limits.
getDeviations() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the deviations used for calculating the forecast confidence limits.
getDeviations() - Method in class com.imsl.stat.AutoARIMA
Returns the deviations used for calculating the forecast confidence limits.
getDeviceMarkerSize() - Method in class com.imsl.chart.Draw
Returns the marker size in device corrdinates.
getDFError() - Method in class com.imsl.stat.NonlinearRegression
Returns the degrees of freedom for error.
getDFFITS() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns DFFITS for an observation.
getDiagonalPivotThreshold() - Method in class com.imsl.math.ComplexSuperLU
Returns the threshold used for a diagonal entry to be an acceptable pivot.
getDiagonalPivotThreshold() - Method in class com.imsl.math.SuperLU
Returns the threshold used for a diagonal entry to be an acceptable pivot.
getDiffMean() - Method in class com.imsl.stat.NormTwoSample
Returns the difference in means, mean of x - mean of y.
getDimension() - Method in class com.imsl.stat.FaureSequence
Returns the dimension of the sequence.
getDimension() - Method in interface com.imsl.stat.RandomSequence
Returns the dimension of the sequence.
getDInitial() - Method in class com.imsl.stat.ARSeasonalFit
Returns the candidate values for d to evaluate.
getDirection() - Method in class com.imsl.chart3d.DirectionalLight
Returns the value of the "Direction" attribute.
getDistanceMatrix() - Method in class com.imsl.stat.Dissimilarities
Returns the distance matrix.
getDistanceMethod() - Method in class com.imsl.stat.Dissimilarities
Returns the method used in computing the dissimilarities or similarities.
getDouble(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a double in the Java programming language.
getDouble(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a double in the Java programming language.
getDoubleAttribute(String, double) - Method in class com.imsl.chart.AbstractChartNode
Convenience routine to get a Double-valued attribute.
getDoubleBuffering() - Method in class com.imsl.chart.ChartNode
Returns the value of the "DoubleBuffering" attribute.
getDown() - Method in class com.imsl.chart.Candlestick
Returns the CandlestickItem for down days.
getDual() - Method in class com.imsl.math.QuadraticProgramming
Returns the dual (Lagrange multipliers).
getDualSolution() - Method in class com.imsl.math.BoundedVariableLeastSquares
Returns the dual solution vector, w.
getDualSolution() - Method in class com.imsl.math.DenseLP
Returns the dual solution.
getDualSolution() - Method in class com.imsl.math.NonNegativeLeastSquares
Returns the dual solution vector, w.
getDummyMethod() - Method in class com.imsl.stat.RegressorsForGLM
Returns the dummy method.
getEffects() - Method in class com.imsl.stat.RegressorsForGLM
Returns the effects.
getEffectsColumns() - Method in class com.imsl.stat.RegressorsForGLM
Returns a mapping of effects to regressor columns.
getEnumValue(String) - Static method in class com.imsl.chart.xml.ChartXML
Returns the int corresponding to an enumeration.
getEpochSize() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the number of sample training patterns in each stage 1 epoch.
getEquilibrate() - Method in class com.imsl.math.ComplexSuperLU
Returns the equilibration flag.
getEquilibrate() - Method in class com.imsl.math.SuperLU
Returns the equilibration flag.
getEquilibrationMethod() - Method in class com.imsl.math.ComplexSuperLU
Returns information on the type of equilibration used before matrix factorization.
getEquilibrationMethod() - Method in class com.imsl.math.SuperLU
Returns information on the type of equilibration used before matrix factorization.
getError() - Method in class com.imsl.datamining.neural.BinaryClassification
Returns the error function for use by QuasiNewtonTrainer for training a binary classification network.
getError() - Method in class com.imsl.datamining.neural.MultiClassification
Returns the error function for use by QuasiNewtonTrainer for training a classification network.
getError() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the function used to compute the error to be minimized.
getErrorEstimate() - Method in class com.imsl.math.EpsilonAlgorithm
Returns the current error estimate.
getErrorEstimate() - Method in class com.imsl.math.HyperRectangleQuadrature
Returns an estimate of the relative error in the computed result.
getErrorEstimate() - Method in class com.imsl.math.Quadrature
Returns an estimate of the relative error in the computed result.
getErrorGradient() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in interface com.imsl.datamining.neural.Trainer
Returns the value of the gradient of the error function with respect to the weights.
getErrorMeanSquare() - Method in class com.imsl.stat.ANOVA
Returns the error mean square.
getErrorNumber() - Method in exception com.imsl.LicenseManagerException
Returns the FlexLM error number for this exception.
getErrorStatus() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the training error status.
getErrorStatus() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Returns the error status from the trainer.
getErrorStatus() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the error status from the trainer.
getErrorStatus() - Method in interface com.imsl.datamining.neural.Trainer
Returns the error status.
getErrorStatus() - Method in class com.imsl.math.MinUnconMultiVar
Returns the non-fatal error status.
getErrorStatus() - Method in class com.imsl.math.NonlinLeastSquares
Get information about the performance of NonlinLeastSquares.
getErrorStatus() - Method in class com.imsl.math.Quadrature
Returns the non-fatal error status.
getErrorStatus() - Method in class com.imsl.stat.NonlinearRegression
Gets information about the performance of NonlinearRegression.
getErrorSumOfSquares() - Method in class com.imsl.math.Spline2DLeastSquares
Returns the weighted error sum of squares.
getErrorValue() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the value of the error function.
getErrorValue() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Returns the final value of the error function.
getErrorValue() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the final value of the error function.
getErrorValue() - Method in interface com.imsl.datamining.neural.Trainer
Returns the value of the error function minimized by the trainer.
getEstimationMethod() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the estimation method used for estimating the autoregressive coefficients.
getEstimationMethod() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the method used for estimating the final autoregressive coefficients for missing value estimation methods AR_1 and AR_P.
getExactMean() - Method in class com.imsl.stat.ContingencyTable
Returns exact mean.
getExactStdev() - Method in class com.imsl.stat.ContingencyTable
Returns exact standard deviation.
getExclude() - Method in class com.imsl.stat.ARSeasonalFit
Returns the current setting for excluding or replacing the inital values in the transformed series.
getExpectedCounts() - Method in class com.imsl.stat.ChiSquaredTest
Returns the expected counts.
getExpectedMean() - Method in class com.imsl.chart.qc.CuSum
Returns the expected mean of all of the data from all of the samples.
getExpectedMean() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the expected (target) mean value.
getExpectedValues() - Method in class com.imsl.stat.ContingencyTable
Returns the expected values of each cell in the table.
getExplode() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Explode" attribute.
getExtendedLikelihoodObservations() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns a vector indicating which observations are included in the extended likelihood.
getF() - Method in class com.imsl.stat.ANOVA
Returns the F statistic.
getFactorLoadings() - Method in class com.imsl.stat.FactorAnalysis
Returns the unrotated factor loadings.
getFarMarkers() - Method in class com.imsl.chart.BoxPlot
Returns the FarMarkers node.
getFarMarkers() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the array of far markers.
getFeature() - Method in exception com.imsl.LicenseManagerException
Returns the name of the feature that could not be licensed.
getFetchDirection() - Method in class com.imsl.io.AbstractFlatFile
Returns the fetch direction for this ResultSet object.
getFetchSize() - Method in class com.imsl.io.AbstractFlatFile
Returns the fetch size for this ResultSet object.
getFillColor() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "FillColor" attribute.
getFillOutlineColor() - Method in class com.imsl.chart.ChartNode
Returns the value of the "FillOutlineColor" attribute.
getFillOutlineType() - Method in class com.imsl.chart.ChartNode
Returns the value of the "FillOutlineType" attribute.
getFillPaint() - Method in class com.imsl.chart.ChartNode
Returns the value of the "FillPaint" attribute.
getFillType() - Method in class com.imsl.chart.ChartNode
Returns the value of the "FillType" attribute.
getFinalActiveConstraints() - Method in class com.imsl.math.MinConGenLin
Returns the indices of the final active constraints.
getFinalActiveConstraintsNum() - Method in class com.imsl.math.MinConGenLin
Returns the final number of active constraints.
getFirstTick() - Method in class com.imsl.chart.Axis1D
Convenience routine to get the "FirstTick" attribute.
getFirstTick() - Method in class com.imsl.chart3d.Axis3D
Convenience routine to get the "FirstTick" attribute.
getFloat(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a float in the Java programming language.
getFloat(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a float in the Java programming language.
getFloor() - Method in class com.imsl.math.ODE
Returns the value used in the norm computation.
getFont() - Method in class com.imsl.chart.AbstractChartNode
Convenience routine which gets a Font object based on the "FontName", "FontStyle" and "FontSize" attributes.
getFontName() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "FontName" attribute.
getFontSize() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "FontSize" attribute.
getFontStyle() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "FontStyle" attribute.
getForecast(int) - Method in class com.imsl.stat.ARAutoUnivariate
Returns forecasts
getForecast(int) - Method in class com.imsl.stat.ARMA
Returns forecasts
getForecast(int) - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns forecasts
getForecast() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns forecasts for the original outlier contaminated series.
getForecast() - Method in class com.imsl.stat.AutoARIMA
Returns forecasts for the original outlier contaminated series.
getForecastGradient(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the derivatives of the outputs with respect to the weights.
getForecastGradient(double[]) - Method in class com.imsl.datamining.neural.Network
Returns the derivatives of the outputs with respect to the weights.
getFormatter() - Static method in class com.imsl.datamining.neural.EpochTrainer
Returns the logging Formatter object.
getFormatter() - Static method in class com.imsl.datamining.neural.LeastSquaresTrainer
Returns the logging Formatter object.
getFormatter() - Static method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the logging formatter object.
getForwardErrorBound() - Method in class com.imsl.math.ComplexSuperLU
Returns the estimated forward error bound for each solution vector.
getForwardErrorBound() - Method in class com.imsl.math.SuperLU
Returns the estimated forward error bound for the solution vector.
getFrequencyColumn() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the column index of x containing the frequency of response for each observation.
getFrequencyColumn() - Method in class com.imsl.stat.ProportionalHazards
Returns the column index of x containing the frequency of response for each observation.
getFrequencyTable() - Method in class com.imsl.stat.TableOneWay
Returns the one-way frequency table.
getFrequencyTable(double, double) - Method in class com.imsl.stat.TableOneWay
Returns a one-way frequency table using known bounds.
getFrequencyTable() - Method in class com.imsl.stat.TableTwoWay
Returns the two-way frequency table.
getFrequencyTable(double, double, double, double) - Method in class com.imsl.stat.TableTwoWay
Compute a two-way frequency table using intervals of equal length and user supplied upper and lower bounds, xLowerBound, xUpperBound, yLowerBound, yUpperBound.
getFrequencyTableUsingClassmarks(double[]) - Method in class com.imsl.stat.TableOneWay
Returns the one-way frequency table using class marks.
getFrequencyTableUsingClassmarks(double[], double[]) - Method in class com.imsl.stat.TableTwoWay
Returns the two-way frequency table using class marks.
getFrequencyTableUsingCutpoints(double[]) - Method in class com.imsl.stat.TableOneWay
Returns the one-way frequency table using cutpoints.
getFrequencyTableUsingCutpoints(double[], double[]) - Method in class com.imsl.stat.TableTwoWay
Returns the two-way frequency table using cutpoints.
getFrom() - Method in class com.imsl.datamining.neural.Link
Returns the origination Node for this Link.
getFTest() - Method in class com.imsl.stat.NormTwoSample
Returns the F test value of the F test for equality of variances.
getFTestDFdenominator() - Method in class com.imsl.stat.NormTwoSample
Returns the denominator degrees of freedom of the F test for equality of variances.
getFTestDFnumerator() - Method in class com.imsl.stat.NormTwoSample
Returns the numerator degrees of freedom of the F test for equality of variances.
getFTestP() - Method in class com.imsl.stat.NormTwoSample
Returns the probability of a larger F in absolute value for the F test for equality of variances, assuming equal variances.
getGaussLegendreDegree() - Method in class com.imsl.math.FeynmanKac
Returns the number of quadrature points used in the Gauss-Legendre quadrature formula.
getGradient() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Gradient" attribute.
getGradient() - Method in class com.imsl.stat.ProportionalHazards
Returns the inverse of the Hessian times the gradient vector, computed at the initial estimates.
getGradients() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the gradients for the final parameter estimates.
getGradientTolerance() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the gradient tolerance for the convergence algorithm.
getGrid() - Method in class com.imsl.chart.Axis1D
Returns the grid node associated with this axis.
getGridPolar() - Method in class com.imsl.chart.Polar
Returns the grid.
getGroupCounts() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the group counts.
getGroupInformation() - Method in class com.imsl.stat.ANOVA
Returns information concerning the groups.
getGroups() - Method in class com.imsl.stat.TableMultiWay
Returns the number of observations (rows) in each group.
getGroupTotal(double) - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the total number in the group for the specified group value.
getGSquared() - Method in class com.imsl.stat.ContingencyTable
Returns the likelihood ratio G2 (chi-squared).
getGSquaredP() - Method in class com.imsl.stat.ContingencyTable
Returns the probability of a larger G2 (chi-squared).
getGuess() - Method in class com.imsl.math.GenMinRes
Returns the initial guess of the solution.
getHeatmapLabels() - Method in class com.imsl.chart.Heatmap
Returns the value of the "HeatmapLabels" attribute.
getHeatmapLegend() - Method in class com.imsl.chart.Heatmap
Returns the heatmap legend.
getHessian() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the Hessian computed at the initial parameter estimates.
getHessian() - Method in class com.imsl.stat.ProportionalHazards
Returns the inverse of the Hessian of the negative of the log-likelihood, computed at the initial estimates.
getHessianOption() - Method in class com.imsl.stat.ProportionalHazards
Returns the boolean used to indicate whether or not to compute the Hessian and gradient at the initial estimates.
getHiddenLayers() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the HiddenLayers in this network.
getHigh() - Method in class com.imsl.chart.ErrorBar
Convenience routine to get the "High" attribute.
getHigh() - Method in class com.imsl.chart.HighLowClose
Convenience routine to get the "High" attribute.
getHistory() - Method in class com.imsl.stat.StepwiseRegression
Returns the stepwise regression history for the independent variables.
getHREF() - Method in class com.imsl.chart.ChartNode
Returns the value of the "HREF" attribute.
getHREF() - Method in class com.imsl.chart.DrawMap
Returns the current HREF string.
getId() - Method in class com.imsl.chart.JspBean
Returns the identifier number for the chart.
getImage() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Image" attribute.
getImageMap() - Method in class com.imsl.chart.JspBean
Returns an HTML for the client-side imagemap.
getImageTag() - Method in class com.imsl.chart.JspBean
Returns an HTML image tag.
getIncidenceMatrix() - Method in class com.imsl.stat.Covariances
Returns the incidence matrix.
getIndependentVariables(int) - Method in class com.imsl.stat.SelectionRegression.Statistics
Returns the identification numbers for the independent variables for the number of variables considered and in the same order as the criteria returned by SelectionRegression.Statistics.getCriterionValues(int).
getIndex() - Method in class com.imsl.datamining.neural.Layer
Returns the index of this Layer.
getIndex() - Method in class com.imsl.stat.Dissimilarities
Returns the indices of the rows (columns) used in computing the distance measure.
getInfo() - Method in class com.imsl.math.SVD
Returns convergence information about S, U, and V.
getInitialCMinus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the initial value of C^{-}.
getInitialCPlus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the initial value of C^{+}.
getInitialEstimates() - Method in class com.imsl.stat.ProportionalHazards
Gets the initial parameter estimates.
getInitialStepsize() - Method in class com.imsl.math.FeynmanKac
Returns the starting step size for the integration.
getInitialStepsize() - Method in class com.imsl.math.ODE
Returns the initial internal step size.
getInnovationVariance() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final estimate for the innovation variance.
getInnovationVariance() - Method in class com.imsl.stat.ARMA
Returns the variance of the random shock.
getInnovationVariance() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the estimated innovation variance of this series.
getInputLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the InputLayer.
getInputLayer() - Method in class com.imsl.datamining.neural.Network
Returns the InputLayer object.
getInt(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as an int in the Java programming language.
getInt(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as an int in the Java programming language.
getIntegerAttribute(String, int) - Method in class com.imsl.chart.AbstractChartNode
Convenience routine to get an Integer-valued attribute.
getIntegrationMethod() - Method in class com.imsl.math.OdeAdamsGear
Returns the integration method used.
getIntercept() - Method in class com.imsl.stat.StepwiseRegression
Returns the intercept.
getIterationCount() - Method in class com.imsl.math.DenseLP
Returns the iteration count.
getIterations() - Method in class com.imsl.math.BoundedVariableLeastSquares
Returns the number of iterations used to find the solution.
getIterations() - Method in class com.imsl.math.ConjugateGradient
Returns the number of iterations needed by the conjugate gradient algorithm.
getIterations() - Method in class com.imsl.math.GenMinRes
Returns the actual number of GMRES iterations used.
getIterations() - Method in class com.imsl.math.MinConNLP
Returns the actual number of iterations used.
getIterations() - Method in class com.imsl.math.MinUnconMultiVar
Returns the number of iterations used to compute a minimum.
getIterations() - Method in class com.imsl.math.NonNegativeLeastSquares
Returns the number of iterations used to find the solution.
getIterativeRefinement() - Method in class com.imsl.math.ComplexSuperLU
Returns a value specifying whether iterative refinement is to be performed or not.
getIterativeRefinement() - Method in class com.imsl.math.SuperLU
Returns a value specifying whether iterative refinement is to be performed or not.
getJackknifeResidual() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Jackknife Residual for an observation.
getJacobi() - Method in class com.imsl.math.ConjugateGradient
Returns the Jacobi preconditioning matrix.
getJacobian() - Method in class com.imsl.math.BoundedLeastSquares
Returns the Jacobian at the approximate solution.
getKeyboard() - Method in class com.imsl.chart3d.Chart3D
Returns the value of the "Keyboard" attribute.
getKnots() - Method in class com.imsl.math.BSpline
Returns a copy of the knot sequence.
getKurtosis() - Method in class com.imsl.stat.Summary
Returns the kurtosis.
getL() - Method in class com.imsl.math.ComplexLU
Returns the lower triangular portion of the LU factorization of A.
getL() - Method in class com.imsl.math.LU
Returns the lower triangular portion of the LU factorization of A.
getLabels() - Method in class com.imsl.chart.AxisLabel
Returns the "Labels" attribute.
getLabels() - Method in class com.imsl.chart.AxisRLabel
Returns the "Labels" attribute.
getLabels() - Method in class com.imsl.chart.Treemap
Returns the value of the "TreemapLabels" attribute.
getLabels() - Method in class com.imsl.chart3d.AxisLabel
Returns the "Labels" attribute.
getLabelType() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "LabelType" attribute.
getLagrangeMultiplierEst() - Method in class com.imsl.math.MinConGenLin
Returns the Lagrange multiplier estimates of the final active constraints.
getLagrangeMultiplierEst() - Method in class com.imsl.math.MinConNLP
Returns the Lagrange multiplier estimates of the constraints.
getLambda() - Method in class com.imsl.chart.qc.EWMA
Returns the value of the attribute "Lambda".
getLargestDiagonalElement() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the largest diagonal element of the Cholesky factor.
getLargestDiagonalElement() - Method in class com.imsl.math.SparseCholesky
Returns the largest diagonal element of the Cholesky factor.
getLastParameterUpdates() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the last parameter updates (excluding step halvings).
getLastUpdates() - Method in class com.imsl.stat.ProportionalHazards
Gets the last parameter updates.
getLayer() - Method in class com.imsl.datamining.neural.Node
Returns the Layer in which this Node exists.
getLeftEndTangent() - Method in class com.imsl.math.CsTCB
Returns the value of the tangent at the leftmost endpoint.
getLeftSons() - Method in class com.imsl.chart.Dendrogram
Convenience routine to get the "LeftSons" attribute.
getLegend() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Legend" attribute.
getLevels() - Method in class com.imsl.chart.Dendrogram
Convenience routine to get the "Levels" attribute.
getLeverage() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Leverage for an observation.
getLicensePath() - Method in exception com.imsl.LicenseManagerException
Returns the license file path for this exception.
getLifeTable() - Method in class com.imsl.stat.LifeTables
Compute a cohort table.
getLightColor() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "LightColor" attribute.
getLightingEnabled() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "LightingEnabled" attribute.
getLikelihood() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final estimate for L=e^{-(mbox{AIC} - 2p)/2}, where p is the AR order, AIC is Akaike's Information Criterion, and L is the likelihood function evaluated for the optimum autoregressive model.
getLikelihood() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the final estimate for -2ln(L), where L is equal to the likelihood function evaluated using the final parameter estimates.
getLineColor() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "LineColor" attribute.
getLineDashPattern() - Method in class com.imsl.chart.ChartNode
Returns the value of the "LineDashPattern" attribute.
getLineWidth() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "LineWidth" attribute.
getLinks() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Return all of the Links in this Network.
getLinks() - Method in class com.imsl.datamining.neural.Network
Returns an array containing the Link objects in the Network.
getListCells() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable
Returns for each row, a list of the levels of nKeys corresponding classification variables that describe a cell.
getLocale() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Locale" attribute.
getLocalizedMessage() - Method in exception com.imsl.LicenseManagerException
Returns the localized error message for this exception.
getLogDeterminant() - Method in class com.imsl.stat.KalmanFilter
Returns the natural log of the product of the nonzero eigenvalues of P where P * sigma2 is the variance-covariance matrix of the observations.
getLogger() - Static method in class com.imsl.datamining.neural.EpochTrainer
Returns the Logger object.
getLogger() - Static method in class com.imsl.datamining.neural.LeastSquaresTrainer
Returns the Logger object.
getLogger() - Static method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the Logger object.
getLogger() - Method in class com.imsl.math.GenMinRes
Returns the logger object.
getLogger() - Method in class com.imsl.math.MinConNLP
Returns the logger object.
getLogger() - Method in class com.imsl.math.ZeroSystem
Returns the logger object.
getLogger() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the logger object.
getLogger() - Method in class com.imsl.stat.ProportionalHazards
Returns the logger object and enables logging.
getLogLikelihood() - Method in class com.imsl.stat.GARCH
Returns the value of Log-likelihood function evaluated at the estimated parameter array.
getLogLikelihood(double) - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the Kaplan-Meier log-likelihood of the group with the specified group value.
getLong(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a long in the Java programming language.
getLong(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a long in the Java programming language.
getLow() - Method in class com.imsl.chart.ErrorBar
Convenience routine to get the "Low" attribute.
getLow() - Method in class com.imsl.chart.HighLowClose
Convenience routine to get the "Low" attribute.
getLowerAdjacentValue() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the lower adjacent value.
getLowerBound(int) - Method in class com.imsl.io.MPSReader
Returns the lower bound for a variable.
getLowerCICommonVariance() - Method in class com.imsl.stat.NormTwoSample
Returns the lower confidence limits for the common, or pooled, variance.
getLowerCIDiff() - Method in class com.imsl.stat.NormTwoSample
Returns the lower confidence limit for the mean of the first population minus the mean of the second for equal or unequal variances depending on the value set by setUnequalVariances.
getLowerCIMean() - Method in class com.imsl.stat.NormOneSample
Returns the lower confidence limit for the mean.
getLowerCIRatioVariance() - Method in class com.imsl.stat.NormTwoSample
Returns the approximate lower confidence limit for the ratio of the variance of the first population to the second.
getLowerCIVariance() - Method in class com.imsl.stat.NormOneSample
Returns the lower confidence limits for the variance.
getLowerControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the lower control limit.
getLowerQuartile() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the lower quartile value.
getLowerRange(int) - Method in class com.imsl.io.MPSReader
Returns the lower range value for a constraint equation.
getMA() - Method in class com.imsl.stat.ARMA
Returns the final moving average parameter estimates.
getMA() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the final moving average parameter estimates.
getMA() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the final moving average parameter estimates.
getMA() - Method in class com.imsl.stat.AutoARIMA
Returns the final moving average parameter estimates of the optimum model.
getMA() - Method in class com.imsl.stat.GARCH
Returns the estimated values of moving average (MA) parameters.
getMahalanobis() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the Mahalanobis distances between the group means.
getMajorTick() - Method in class com.imsl.chart.Axis1D
Returns the major tick node associated with this axis.
getMajorTick() - Method in class com.imsl.chart3d.Axis3D
Returns the major tick node associated with this axis.
getMap() - Method in class com.imsl.chart.DrawMap
Returns the body of the HTML imagemap.
getMapName() - Method in class com.imsl.chart.JspBean
Returns the name of the client-size imagemap.
getMarkerColor() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "MarkerColor" attribute.
getMarkerDashPattern() - Method in class com.imsl.chart.ChartNode
Returns the value of the "MarkerPattern" attribute.
getMarkerPulsingCycle() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerPulsingCycle" attribute.
getMarkerPulsingCycleOffset() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerPulsingCycleOffset" attribute.
getMarkerPulsingMaximumScale() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerPulsingMaximumScale" attribute.
getMarkerPulsingMinimumScale() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerPulsingMinimumScale" attribute.
getMarkerRotatingAxis() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerRotatingAxis" attribute.
getMarkerRotatingCycle() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerRotatingCycle" attribute.
getMarkerRotatingCycleOffset() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerRotatingCycleOffset" attribute.
getMarkerSize() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "MarkerSize" attribute.
getMarkerThickness() - Method in class com.imsl.chart.ChartNode
Returns the value of the "MarkerThickness" attribute.
getMarkerType() - Method in class com.imsl.chart.ChartNode
Returns the value of the "MarkerType" attribute.
getMarkerType() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "MarkerType" attribute.
getMaterial() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Material" attribute.
getMaxClass() - Method in class com.imsl.stat.ProportionalHazards
Returns the upper bound used on the sum of the number of distinct values found among the classification variables in x.
getMaxDifference() - Method in class com.imsl.stat.NormalityTest
Returns the maximum absolute difference between the empirical and the theoretical distributions for the Lilliefors test.
getMaxEvaluations() - Method in class com.imsl.math.ZerosFunction
Returns the maximum number of function evaluations allowed.
getMaximum() - Method in class com.imsl.stat.Summary
Returns the maximum.
getMaximum() - Method in class com.imsl.stat.TableOneWay
Returns maximum value of x.
getMaximumBDFOrder() - Method in class com.imsl.math.FeynmanKac
Returns the maximum order of the BDF formulas.
getMaximumDifference() - Method in class com.imsl.stat.KolmogorovOneSample
Returns D^{+}, the maximum difference between the theoretical and empirical CDF's.
getMaximumDifference() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns D^{+}, the maximum difference between the theoretical and empirical CDF's.
getMaximumFunctionEvaluations() - Method in class com.imsl.math.OdeAdamsGear
Returns the maximum number of function evaluations of y' allowed.
getMaximumLikelihood() - Method in class com.imsl.stat.ProportionalHazards
Returns the maximized log-likelihood.
getMaximumStepsize() - Method in class com.imsl.math.FeynmanKac
Returns the maximum internal step size used by the integrator.
getMaximumStepsize() - Method in class com.imsl.math.ODE
Returns the maximum internal step size.
getMaximumTime() - Method in class com.imsl.math.MinConNLP
Returns the maximum time allowed for the solve step.
getMaximumValue() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the maximum value of the observations.
getMaximumValue() - Method in class com.imsl.chart.qc.ControlLimit
Returns the maximum value of this control limit line.
getMaximumX() - Method in class com.imsl.stat.TableTwoWay
Returns the maximum value of x.
getMaximumY() - Method in class com.imsl.stat.TableTwoWay
Returns the maximum value of y.
getMaxIterations() - Method in class com.imsl.math.ConjugateGradient
Returns the maximum number of iterations allowed.
getMaxIterations() - Method in class com.imsl.math.Eigen
Returns the maximum number of iterations.
getMaxIterations() - Method in class com.imsl.math.GenMinRes
Returns the maximum number of iterations allowed.
getMaxIterations() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the value currently being used as the maximum number of iterations allowed in the nonlinear equation solver used in both the method of moments and least-squares algorithms.
getMaxIterations() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the maximum number of estimation iterations used by missing value estimation methods AR_1 and AR_P.
getMaxIterations() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the maximum number of iterations.
getMaxIterations() - Method in class com.imsl.stat.ProportionalHazards
Return the maximum number of iterations allowed.
getMaxKrylovDim() - Method in class com.imsl.math.GenMinRes
Returns the maximum Krylov subspace dimension, i.e., the maximum allowable number of GMRES iterations allowed before restarting.
getMaxlag() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the current value used to represent the maximum number of autoregressive lags to achieve the minimum AIC.
getMaxlag() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the current value of autoregressive lags used in the AR_P estimation method.
getMaxlag() - Method in class com.imsl.stat.ARSeasonalFit
Returns the maximum lag used to fit the AR(p) model.
getMaxOrder() - Method in class com.imsl.math.OdeAdamsGear
Returns the highest order formula to use of implicit METHOD_ADAMS type or METHOD_BDF type.
getMaxSteps() - Method in class com.imsl.math.FeynmanKac
Returns the maximum number of internal steps allowed.
getMaxSteps() - Method in class com.imsl.math.ODE
Returns the maximum number of internal steps allowed.
getMean() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the mean used to center the time series z.
getMean() - Method in class com.imsl.stat.ARMA
Returns an update of the mean of the time series z.
getMean() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the mean value used to center the series.
getMean() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the mean used to center the time series.
getMean() - Method in class com.imsl.stat.AutoCorrelation
Returns the mean of the time series x.
getMean() - Method in class com.imsl.stat.LogNormalDistribution
Returns the lognormal probability distribution mean parameter.
getMean() - Method in class com.imsl.stat.NormalDistribution
Returns the population mean of xData.
getMean() - Method in class com.imsl.stat.NormOneSample
Returns the mean of the sample.
getMean() - Method in class com.imsl.stat.Summary
Returns the population mean.
getMeanOfY() - Method in class com.imsl.stat.ANOVA
Returns the mean of the response (dependent variable).
getMeans(double[][], int[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns a table of means for each continuous attribute in continuousData segmented by the target classes in classificationData.
getMeans() - Method in class com.imsl.stat.ANCOVA
Returns a matrix containing the unadjusted means for the covariates and the response variate and the means for the response variate adjusted for the covariates.
getMeans() - Method in class com.imsl.stat.ANOVAFactorial
Returns the subgroup means.
getMeans() - Method in class com.imsl.stat.Covariances
Returns the means of the variables in x.
getMeans() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the variable means.
getMeans() - Method in class com.imsl.stat.ProportionalHazards
Returns the means of the design variables.
getMeanSampleSize() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the value of the attribute "MeanSampleSize".
getMeanX() - Method in class com.imsl.stat.CrossCorrelation
Returns the mean of the time series x.
getMeanX() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the mean of each channel of x.
getMeanX() - Method in class com.imsl.stat.NormTwoSample
Returns the mean of the first sample, x.
getMeanY() - Method in class com.imsl.stat.CrossCorrelation
Returns the mean of the time series y.
getMeanY() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the mean of each channel of y.
getMeanY() - Method in class com.imsl.stat.NormTwoSample
Returns the mean of the second sample, y.
getMedian() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the median value.
getMedianLowerConfidenceInterval() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the lower confidence interval for the median.
getMedianUpperConfidenceInterval() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the upper confidence interval for the median.
getMetaData() - Method in class com.imsl.io.AbstractFlatFile
Retrieves the number, types and properties of this ResultSet object's columns.
getMethod() - Method in class com.imsl.math.GenMinRes
Returns the implementation method to be used.
getMethod() - Method in class com.imsl.stat.ClusterHierarchical
Returns the clustering method used.
getMinimum() - Method in class com.imsl.stat.Summary
Returns the minimum.
getMinimum() - Method in class com.imsl.stat.TableOneWay
Returns the minimum value of x.
getMinimumDifference() - Method in class com.imsl.stat.KolmogorovOneSample
Returns D^{-}, the minimum difference between the theoretical and empirical CDF's.
getMinimumDifference() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns D^{-}, the minimum difference between the theoretical and empirical CDF's.
getMinimumStepsize() - Method in class com.imsl.math.ODE
Returns the minimum internal step size.
getMinimumValue() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the minimum value of the observations.
getMinimumValue() - Method in class com.imsl.chart.qc.ControlLimit
Returns the minimum value of this control limit line.
getMinimumX() - Method in class com.imsl.stat.TableTwoWay
Returns the minimum value of x.
getMinimumY() - Method in class com.imsl.stat.TableTwoWay
Returns the minimum value of y.
getMinorTick() - Method in class com.imsl.chart.Axis1D
Returns the minor tick node associated with this axis.
getMissingTimes() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns an int array of the times with missing values.
getMissingValueMethod() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the current missing value estimation method.
getModelCoefficients() - Method in class com.imsl.stat.ANCOVA
Returns a matrix containing statistics for the regression coefficients for the model assuming parallelism.
getModelErrorStdev() - Method in class com.imsl.stat.ANOVA
Returns the estimated standard deviation of the model error.
getModelMeanSquare() - Method in class com.imsl.stat.ANOVA
Returns the model mean square.
getMonthBasis() - Method in class com.imsl.finance.DayCountBasis
Returns the (days in month) portion of the Day Count Basis.
getMRBar() - Method in class com.imsl.chart.qc.XmR
Returns the expected mean of of all of the moving ranges of two observations.
getName() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Name" attribute.
getName() - Method in class com.imsl.io.MPSReader
Returns the name of the MPS problem.
getName() - Method in class com.imsl.io.MPSReader.Row
Returns the name of this row.
getNameBounds() - Method in class com.imsl.io.MPSReader
Returns the name of the BOUNDS set.
getNameColumn(int) - Method in class com.imsl.io.MPSReader
Returns the name of a constraint column.
getNameObjective() - Method in class com.imsl.io.MPSReader
Returns the name of the free row containing the objective.
getNameRanges() - Method in class com.imsl.io.MPSReader
Returns the name of the RANGES set.
getNameRHS() - Method in class com.imsl.io.MPSReader
Returns the name of the RHS section.
getNameRow(int) - Method in class com.imsl.io.MPSReader
Returns the name of a contraint row.
getNCells() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable
Returns the number of non-empty cells.
getNetwork() - Method in class com.imsl.datamining.neural.BinaryClassification
Returns the network being used for classification.
getNetwork() - Method in class com.imsl.datamining.neural.MultiClassification
Returns the network being used for classification.
getNLost() - Method in class com.imsl.stat.ARSeasonalFit
Returns the number of values in the initial part of the series lost to differencing.
getNMinus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns N^{-}, the number of consecutive periods that the cusums C_i^{-} have been nonzero.
getNode() - Method in class com.imsl.chart.PickEvent
Gets this ChartNode.
getNodes() - Method in class com.imsl.datamining.neural.InputLayer
Return the Perceptrons in the InputLayer.
getNodes() - Method in class com.imsl.datamining.neural.Layer
Return a list of the Perceptrons in this Layer.
getNodes() - Method in class com.imsl.datamining.neural.OutputLayer
Return the Perceptrons in the OutputLayer.
getNorm() - Method in class com.imsl.math.ODE
Returns the switch for determining the error norm.
getNormalScores(double[]) - Method in class com.imsl.stat.Ranks
Gets the expected value of normal order statistics (for tied observations, the average of the expected normal scores).
getNotch() - Method in class com.imsl.chart.BoxPlot
Gets the "Notch" attribute value.
getNPlus() - Method in class com.imsl.chart.qc.CuSumStatus
Returns N^{+}, the number of consecutive periods that the cusums C_i^{+} have been nonzero.
getNRowsMissing() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the number of rows of data in x that contain missing values in one or more specific columns of x.
getNumber() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Number" attribute.
getNumberAtRisk() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the number of individuals at risk at each failure point.
getNumberFormat() - Method in class com.imsl.math.PrintMatrixFormat
Returns the NumberFormat to be used in formatting double and Complex entries.
getNumberGridPointsX() - Method in class com.imsl.chart3d.Surface
Returns the value of the "NumberGridPointsX" attribute.
getNumberGridPointsY() - Method in class com.imsl.chart3d.Surface
Returns the value of the "NumberGridPointsY" attribute.
getNumberMissing() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the number of missing values in the original series
getNumberMissing() - Method in class com.imsl.stat.KolmogorovOneSample
Returns the number of missing values in the data.
getNumberMissingX() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns the number of missing values in the x sample.
getNumberMissingY() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns the number of missing values in the y sample.
getNumberObservations() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the number of observations.
getNumberOfBackcasts() - Method in class com.imsl.stat.ARMA
Returns the number of backcasts used to calculate the AR coefficients for the time series z.
getNumberOfBinaryConstraints() - Method in class com.imsl.io.MPSReader
Returns the number of binary constraints.
getNumberOfClasses() - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter
Retrieves the number of classes in the nominal variable.
getNumberOfClasses() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Retrieves the number of categories associated with this ordinal variable.
getNumberOfCoefficients() - Method in class com.imsl.stat.ProportionalHazards
Returns the number of estimated coefficients in the model.
getNumberOfColumns() - Method in class com.imsl.io.MPSReader
Returns the number of columns in the constraint matrix.
getNumberOfColumns() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the number of columns in the matrix.
getNumberOfColumns() - Method in class com.imsl.math.SparseMatrix
Returns the number of columns in the matrix.
getNumberOfEpochs() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the number of epochs used during stage I training.
getNumberOfEvaluations() - Method in class com.imsl.math.ZerosFunction
Returns the actual number of function evaluations performed.
getNumberOfFailures() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the number of failures which occurred at each failure point.
getNumberOfFcnEvals() - Method in class com.imsl.math.OdeAdamsGear
Returns the number of function evaluations of y' made.
getNumberOfInputs() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the number of inputs to the Network.
getNumberOfInputs() - Method in class com.imsl.datamining.neural.Network
Returns the number of Network inputs.
getNumberOfIntegerConstraints() - Method in class com.imsl.io.MPSReader
Returns the number of integer constraints.
getNumberOfJacobianEvals() - Method in class com.imsl.math.OdeAdamsGear
Returns the number of Jacobian matrix evaluations used.
getNumberOfLinks() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the number of Links in the Network.
getNumberOfLinks() - Method in class com.imsl.datamining.neural.Network
Returns the number of Network Links among the nodes.
getNumberOfMissing() - Method in class com.imsl.stat.ANCOVA
Returns the number of cases with missing values in covariates or responses.
getNumberOfMissingRows() - Method in class com.imsl.stat.RegressorsForGLM
Returns the number of rows in the regressors matrix containing NaN (not a number).
getNumberOfNonZeros() - Method in class com.imsl.io.MPSReader
Returns the number of nonzeros in the constraint matrix.
getNumberOfNonZeros() - Method in class com.imsl.io.MPSReader.Row
Returns the number of nonzero elements in this row.
getNumberOfNonzeros() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the number of nonzeros in the Cholesky factor.
getNumberOfNonZeros() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the number of nonzeros in the matrix.
getNumberOfNonzeros() - Method in class com.imsl.math.SparseCholesky
Returns the number of nonzeros in the Cholesky factor.
getNumberOfNonZeros() - Method in class com.imsl.math.SparseMatrix
Returns the number of nonzeros in the matrix.
getNumberOfOutliers() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the number of outliers detected.
getNumberOfOutliers() - Method in class com.imsl.stat.AutoARIMA
Returns the number of outliers detected.
getNumberOfOutputs() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the number of outputs from the Network.
getNumberOfOutputs() - Method in class com.imsl.datamining.neural.Network
Returns the number of Network output Perceptrons.
getNumberOfPoints() - Method in class com.imsl.stat.KaplanMeierECDF
Retrieves the number of points in the empirical CDF
getNumberOfRegressors() - Method in class com.imsl.stat.RegressorsForGLM
Returns the number regressors.
getNumberOfRoots() - Method in class com.imsl.math.ZerosFunction
Returns the requested number of roots to be found.
getNumberOfRootsFound() - Method in class com.imsl.math.ZerosFunction
Returns the number of zeros found.
getNumberOfRows() - Method in class com.imsl.io.MPSReader
Returns the number of rows in the constraint matrix.
getNumberOfRows() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the number of rows in the matrix.
getNumberOfRows() - Method in class com.imsl.math.SparseMatrix
Returns the number of rows in the matrix.
getNumberOfRowsMissing() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the number of rows of data encountered containing missing values (Double.NaN).
getNumberOfRowsMissing() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the number of rows of data in x that contain missing values in one or more specific columns of x.
getNumberOfSteps() - Method in class com.imsl.math.OdeAdamsGear
Returns the number of internal steps taken.
getNumberOfThreads() - Method in class com.imsl.datamining.neural.EpochTrainer
Gets the number of threads to use during stage I training.
getNumberOfTies() - Method in class com.imsl.stat.KolmogorovOneSample
Returns the number of ties in the data.
getNumberOfWeights() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the number of weights in the Network.
getNumberOfWeights() - Method in class com.imsl.datamining.neural.Network
Returns the number of weights in the Network.
getNumberRowsMissing() - Method in class com.imsl.stat.ProportionalHazards
Returns the number of rows of data in x that contain missing values in one or more specific columns of x.
getNumericFactor() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the numeric Cholesky factor.
getNumericFactor() - Method in class com.imsl.math.SparseCholesky
Returns the numeric Cholesky factor.
getNumericFactorizationMethod() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the method used in the numerical factorization of the permuted input matrix.
getNumericFactorizationMethod() - Method in class com.imsl.math.SparseCholesky
Returns the method used in the numerical factorization of the permuted input matrix.
getNumPositiveDev() - Method in class com.imsl.stat.SignTest
Returns the number of positive differences.
getNumRowMissing() - Method in class com.imsl.stat.Covariances
Returns the total number of observations that contain any missing values (Double.NaN).
getNumZeroDev() - Method in class com.imsl.stat.SignTest
Returns the number of zero differences.
getNvalues() - Method in class com.imsl.stat.TableMultiWay.BalancedTable
Returns an array of length nKeys containing in its i-th element (i=0,1,...nKeys-1), the number of levels or categories of the i-th classification variable (column).
getObject(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(int, Map) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(String, Map) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(int) - Method in class com.imsl.io.FlatFile
Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObjective() - Method in class com.imsl.io.MPSReader
Returns the objective as a Row.
getObjectiveCoefficients() - Method in class com.imsl.io.MPSReader
Returns the coefficents of the objective row.
getObjectiveValue() - Method in class com.imsl.math.MinConGenLin
Returns the value of the objective function.
getObservations() - Method in class com.imsl.stat.Covariances
Returns the sum of the frequencies.
getObservationsLost() - Method in class com.imsl.stat.Difference
Returns the number of observations lost because of differencing the time series.
getObservedResponse() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the observed response for an observation.
getObsPerCluster(int) - Method in class com.imsl.stat.ClusterHierarchical
Returns the number of observations in each cluster.
getOffset() - Method in class com.imsl.chart.Text
Returns the offset.
getOmegaWeights() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the omega weights for the detected outliers.
getOneSidedPValue() - Method in class com.imsl.stat.KolmogorovOneSample
Probability of the statistic exceeding D under the null hypothesis of equality and against the one-sided alternative.
getOneSidedPValue() - Method in class com.imsl.stat.KolmogorovTwoSample
Probability of the statistic exceeding D under the null hypothesis of equality and against the one-sided alternative.
getOpen() - Method in class com.imsl.chart.HighLowClose
Gets the value of the attribute "Open".
getOptimalValue() - Method in class com.imsl.math.DenseLP
Returns the optimal value of the objective function.
getOptimizedCriterion() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the optimized criterion.
getOptimumD() - Method in class com.imsl.stat.ARSeasonalFit
Returns the optimum values for d selected among the candidates in dInitial.
getOptimumModelOrder() - Method in class com.imsl.stat.AutoARIMA
Returns the order (p,0,q)times(0,d,0)_s of the optimum model.
getOptimumS() - Method in class com.imsl.stat.ARSeasonalFit
Returns the optimum values for s selected among the candidates in sInitial.
getOrbit() - Method in class com.imsl.chart3d.Chart3D
Returns the value of the "Orbit" attribute.
getOrder() - Method in class com.imsl.chart.Dendrogram
Convenience routine to get the "Order" attribute.
getOrder() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the order of the AR model selected with the minimum AIC.
getOrientation() - Method in class com.imsl.chart.Treemap
Gets the value of the "Orientation" attribute.
getOutlierFreeForecast() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns forecasts for the outlier free series.
getOutlierFreeForecast() - Method in class com.imsl.stat.AutoARIMA
Returns forecasts for the outlier free series.
getOutlierFreeSeries() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the outlier free series.
getOutlierFreeSeries() - Method in class com.imsl.stat.AutoARIMA
Returns the outlier free series.
getOutlierStatistics() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the outlier statistics.
getOutlierStatistics() - Method in class com.imsl.stat.AutoARIMA
Returns the outlier statistics.
getOutputLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the OutputLayer.
getOutputLayer() - Method in class com.imsl.datamining.neural.Network
Returns the OutputLayer.
getOutsideMarkers() - Method in class com.imsl.chart.BoxPlot
Returns the OutsideMarkers node.
getOutsideMarkers() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the array of outside markers.
getP() - Method in class com.imsl.stat.ANOVA
Returns the p-value.
getP() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the number of autoregressive terms in the ARMA model
getP() - Method in class com.imsl.stat.ChiSquaredTest
Returns the p-value for the chi-squared statistic.
getP() - Method in class com.imsl.stat.ContingencyTable
Returns the Pearson chi-squared p-value for independence of rows and columns.
getPaint() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Paint" attribute.
getPanel() - Method in class com.imsl.chart.JFrameChart
Returns the JPanelChart into which the chart is drawn.
getParamEstimatesCovariance() - Method in class com.imsl.stat.ARMA
Returns the covariances of parameter estimates.
getParameters() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the parameter estimates and associated statistics.
getParameters() - Method in class com.imsl.stat.GammaDistribution
Returns the current parameters of the gamma probability density function.
getParameters() - Method in class com.imsl.stat.LogNormalDistribution
Returns the current parameters of the lognormal probability density function
getParameters() - Method in class com.imsl.stat.NormalDistribution
Returns the current parameters of the normal probability density function.
getParameters() - Method in class com.imsl.stat.PoissonDistribution
Returns the current parameters of the Poisson probability density function.
getParameters() - Method in interface com.imsl.stat.ProbabilityDistribution
Returns the current parameters of the probability density function.
getParameterStatistics() - Method in class com.imsl.stat.ProportionalHazards
Returns the parameter estimates and associated statistics.
getParameterUpdates() - Method in class com.imsl.stat.FactorAnalysis
Returns the parameter updates.
getParent() - Method in class com.imsl.chart.ChartNode
Returns the parent of this node.
getParent() - Method in class com.imsl.chart3d.ChartNode3D
Returns the parent of this node.
getPartialAutoCorrelations() - Method in class com.imsl.stat.AutoCorrelation
Returns the sample partial autocorrelation function of the stationary time series x.
getPartialCorrelationMatrix() - Method in class com.imsl.stat.PartialCovariances
Returns the partial correlation matrix.
getPartialCovarianceMatrix() - Method in class com.imsl.stat.PartialCovariances
Returns the partial covariance matrix.
getPartialDegreesOfFreedom() - Method in class com.imsl.stat.PartialCovariances
Returns the degrees of freedom in the test that the partial correlation (covariance) is zero.
getPercentageFactor() - Method in class com.imsl.math.NumericalDerivatives
Returns the percentage factor for differencing.
getPercentages() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Retrieves the cumulative percentages used for encoding and decoding.
getPercents() - Method in class com.imsl.stat.FactorAnalysis
Returns the cumulative percent of the total variance explained by each principal component.
getPerceptrons() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the Perceptrons in this Network.
getPerceptrons() - Method in class com.imsl.datamining.neural.Network
Returns an array containing the Perceptrons in the Network.
getPerformanceTuningParameters(int) - Method in class com.imsl.math.ComplexSuperLU
Returns a performance tuning parameter value.
getPerformanceTuningParameters(int) - Method in class com.imsl.math.SuperLU
Returns a performance tuning parameter value.
getPermutationMatrix() - Method in class com.imsl.math.ComplexLU
Returns the permutation matrix which results from the LU factorization of A.
getPermutationMatrix() - Method in class com.imsl.math.LU
Returns the permutation matrix which results from the LU factorization of A.
getPermute() - Method in class com.imsl.math.QR
Returns an integer vector containing information about the permutation of the elements of the matrix during pivoting.
getPhi() - Method in class com.imsl.stat.ContingencyTable
Returns phi.
getPieSlice() - Method in class com.imsl.chart.Pie
Returns the PieSlice objects.
getPieSlice(int) - Method in class com.imsl.chart.Pie
Returns a specified PieSlice.
getPivotGrowth() - Method in class com.imsl.math.ComplexSuperLU
Returns the reciprocal pivot growth factor flag.
getPivotGrowth() - Method in class com.imsl.math.SuperLU
Returns the reciprocal pivot growth factor flag.
getPooledVariance() - Method in class com.imsl.stat.NormTwoSample
Returns the Pooled variance for the two samples.
getPopulationTable(int[]) - Method in class com.imsl.stat.LifeTables
Compute a population table.
getPosition() - Method in class com.imsl.chart3d.ColormapLegend
Returns the position of the legend.
getPosition() - Method in class com.imsl.chart3d.PointLight
Returns the value of the "Position" attribute.
getPreconditionerSolves() - Method in class com.imsl.math.GenMinRes
Returns the total number of GMRES right preconditioner solves.
getPredictedClass() - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns the predicted classification for each training pattern.
getPredictedResponse() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the predicted response for an observation.
getPredictionError() - Method in class com.imsl.stat.KalmanFilter
Returns the one-step-ahead prediction error.
getPredictionInterval() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Prediction Interval for an observation.
getPrimalSolution() - Method in class com.imsl.math.DenseLP
Returns the solution x of the linear programming problem.
getPrior() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the prior probabilities.
getProbabilities() - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns the predicted classification probabilities for each target class.
getProbability() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns the posterior probabilities for each observation.
getProduct() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the inverse of the Hessian times the gradient vector computed at the input parameter estimates.
getProducts() - Method in class com.imsl.math.GenMinRes
Returns the total number of GMRES matrix-vector products used.
getPsiWeights() - Method in class com.imsl.stat.ARMA
Returns the psi weights of the infinite order moving average form of the model.
getPsiWeights() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the psi weights used for calculating forecasts from the infinite order moving average form of the ARMA model.
getPsiWeights() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the psi weights of the infinite order moving average form of the model.
getPsiWeights() - Method in class com.imsl.stat.AutoARIMA
Returns the psi weights of the infinite order moving average form of the model.
getPValue(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests
Returns the p-value for the two-sided test.
getPValue(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests
Returns the p-value for the two-sided test H_0 : {
  beta} = 0 vs.
getPValues() - Method in class com.imsl.stat.PartialCovariances
Calculates the p-values for testing the null hypothesis that the associated partial covariance/correlation is zero.
getQ() - Method in class com.imsl.math.QR
Returns the orthogonal or unitary matrix Q.
getQ() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the number of moving average terms in the ARMA model
getQ() - Method in class com.imsl.stat.EmpiricalQuantiles
Returns the empirical quantiles.
getR() - Method in class com.imsl.math.Cholesky
Returns the R matrix that results from the Cholesky factorization.
getR() - Method in class com.imsl.math.QR
Returns the upper trapezoidal matrix R.
getR() - Method in class com.imsl.stat.ANCOVA
Returns the R matrix from the QR decomposition.
getR() - Method in class com.imsl.stat.LinearRegression
Returns a copy of the R matrix.
getR() - Method in class com.imsl.stat.NonlinearRegression
Returns a copy of the R matrix.
getRadialFunction() - Method in class com.imsl.math.RadialBasis
Returns the radial function.
getRadius(int) - Method in class com.imsl.math.ZeroPolynomial
Returns an a-posteriori absolute error bound on the root.
getRandom() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the random number generator used to perturb the stage 1 guesses.
getRandomSampleIndicies() - Method in class com.imsl.datamining.neural.EpochTrainer
Gets the random number generators used to select random training patterns in stage 1.
getRank() - Method in class com.imsl.math.QR
Returns the rank of the matrix used to construct this instance.
getRank() - Method in class com.imsl.math.SVD
Returns the rank of the matrix used to construct this instance.
getRank() - Method in class com.imsl.stat.KalmanFilter
Returns the rank of the variance-covariance matrix for all the observations.
getRank() - Method in class com.imsl.stat.LinearRegression
Returns the rank of the matrix.
getRank() - Method in class com.imsl.stat.NonlinearRegression
Returns the rank of the matrix.
getRanks(double[]) - Method in class com.imsl.stat.Ranks
Gets the rank for each observation.
getRbar() - Method in class com.imsl.chart.qc.XbarR
Returns the value of the "Rbar" attribute, the mean of the ranges for a series of samples.
getReciprocalPivotGrowthFactor() - Method in class com.imsl.math.ComplexSuperLU
Returns the reciprocal pivot growth factor.
getReciprocalPivotGrowthFactor() - Method in class com.imsl.math.SuperLU
Returns the reciprocal pivot growth factor.
getRef(int) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Ref object in the Java programming language.
getRef(String) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a Ref object in the Java programming language.
getReference() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Reference" attribute.
getRegressors() - Method in class com.imsl.stat.RegressorsForGLM
Returns the regressor array.
getRelativeBackwardError() - Method in class com.imsl.math.ComplexSuperLU
Returns the componentwise relative backward error of the solution vector.
getRelativeBackwardError() - Method in class com.imsl.math.SuperLU
Returns the componentwise relative backward error of the solution vector.
getRelativeError(double) - Method in class com.imsl.math.ConjugateGradient
Returns the relative error used for stopping the algorithm.
getRelativeError() - Method in class com.imsl.math.GenMinRes
Returns the stopping tolerance.
getRelativeError() - Method in class com.imsl.stat.ARMAEstimateMissing
Returns the relative error used for the METHOD_OF_MOMENTS and LEAST_SQARES estimation methods.
getRelativeErrorTolerances() - Method in class com.imsl.math.FeynmanKac
Returns relative error tolerances.
getRelativeH() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the value for relative h.
getResidual() - Method in class com.imsl.stat.ARMA
Returns the residuals.
getResidual() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the residuals.
getResidual() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Residual for an observation.
getResidualNorm() - Method in class com.imsl.math.BoundedVariableLeastSquares
Returns the euclidean norm of the residual vector, |Ax-b|^2.
getResidualNorm() - Method in class com.imsl.math.GenMinRes
Returns the final residual norm, {Vert b-Ax Vert}_2 .
getResidualNorm() - Method in class com.imsl.math.NonNegativeLeastSquares
Returns the euclidean norm of the residual vector, |Ax-b|^2.
getResiduals() - Method in class com.imsl.math.BoundedLeastSquares
Returns the residuals at the approximate solution.
getResiduals() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the current values of the vector of residuals.
getResiduals() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the current values of the vector of residuals.
getResiduals() - Method in class com.imsl.stat.AutoARIMA
Returns the residuals.
getResidualStandardError() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the residual standard error of the outlier free series.
getResidualStandardError() - Method in class com.imsl.stat.AutoARIMA
Returns the residual standard error of the outlier free series.
getResidualUpdating() - Method in class com.imsl.math.GenMinRes
Returns the residual updating method to be used.
getResponseColumn() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the column index of x containing the response time for each observation.
getResponseColumn() - Method in class com.imsl.stat.ProportionalHazards
Returns the column index of x containing the response time for each observation.
getRightEndTangent() - Method in class com.imsl.math.CsTCB
Returns the value of the tangent at the rightmost endpoint.
getRightSons() - Method in class com.imsl.chart.Dendrogram
Convenience routine to get the "RightSons" attribute.
getRoot(int) - Method in class com.imsl.math.ZeroPolynomial
Returns a zero of the polynomial.
getRoots() - Method in class com.imsl.math.ZeroPolynomial
Returns the zeros of the polynomial.
getRow() - Method in class com.imsl.io.AbstractFlatFile
Retrieves the current row number.
getRow(int) - Method in class com.imsl.io.MPSReader
Returns a row of the constraint matrix or a free row.
getRow() - Method in class com.imsl.stat.Dissimilarities
Returns a boolean indicating whether distances are computed between rows or columns of x.
getRowCoefficients(int) - Method in class com.imsl.io.MPSReader
Returns the coefficents of a row.
getRSquared() - Method in class com.imsl.stat.ANOVA
Returns the R-squared (in percent).
getS() - Method in class com.imsl.math.SVD
Returns the singular values.
getSafePixel(Color) - Static method in class com.imsl.chart.WebSafeImageFilter
Returns the Web-safe color nearest the given color.
getSampleSize() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the value of the attribute "SampleSize".
getSampleStandardDeviation() - Method in class com.imsl.stat.Summary
Returns the sample standard deviation.
getSampleVariance() - Method in class com.imsl.stat.Summary
Returns the sample variance.
getSavageScores(double[]) - Method in class com.imsl.stat.Ranks
Gets the Savage scores (the expected value of exponential order statistics).
getScale() - Method in class com.imsl.math.ODE
Returns the scaling factor.
getScaleFont() - Method in class com.imsl.chart.Draw
Returns the factor by which fonts are to be scaled.
getScaleParameter() - Method in class com.imsl.stat.GammaDistribution
Returns the maximum-likelihood estimate found for the gamma scale parameter.
getScalingFactors() - Method in class com.imsl.math.NumericalDerivatives
Returns the scaling factors for the y values.
getScalingOption() - Method in class com.imsl.stat.Dissimilarities
Returns the scaling option.
getScreenAxis() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ScreenAxis" attribute.
getScreenSize() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ScreenSize" attribute.
getScreenViewport() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Viewport" attribute scaled by the screen size.
getShapeParameter() - Method in class com.imsl.stat.GammaDistribution
Returns the maximum-likelihood estimate found for the gamma shape parameter.
getShapiroWilkW() - Method in class com.imsl.stat.NormalityTest
Returns the Shapiro-Wilk W statistic for the Shapiro-Wilk W test.
getShort(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a short in the Java programming language.
getShort(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a short in the Java programming language.
getSigma() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the standard deviation of the data.
getSigma() - Method in class com.imsl.stat.GARCH
Returns the estimated value of sigma squared.
getSInitial() - Method in class com.imsl.stat.ARSeasonalFit
Returns the the candidate values for s to evaluate.
getSize() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Size" attribute.
getSize(Text) - Method in class com.imsl.chart.Draw
Returns the size of the bounding box for a text object.
getSize() - Method in class com.imsl.chart.JspBean
Returns the size of the generated image.
getSkewness() - Method in class com.imsl.stat.Summary
Returns the skewness.
getSkip() - Method in class com.imsl.stat.FaureSequence
Returns the number of points skipped at the beginning of the sequence.
getSkipWeekends() - Method in class com.imsl.chart.ChartNode
Returns the value of the "SkipWeekends" attribute.
getSlackValue() - Method in class com.imsl.chart.qc.CuSumStatus
Returns the slack value.
getSmallestDiagonalElement() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the smallest diagonal element of the Cholesky factor.
getSmallestDiagonalElement() - Method in class com.imsl.math.SparseCholesky
Returns the smallest diagonal element of the Cholesky factor.
getSolution() - Method in class com.imsl.math.BoundedLeastSquares
Returns the solution.
getSolution() - Method in class com.imsl.math.BoundedVariableLeastSquares
Returns the solution to the problem.
getSolution() - Method in class com.imsl.math.MinConGenLin
Returns the computed solution.
getSolution() - Method in class com.imsl.math.MinConNLP
Returns the last computed solution.
getSolution() - Method in class com.imsl.math.NonNegativeLeastSquares
Returns the solution to the problem, x.
getSolution() - Method in class com.imsl.math.QuadraticProgramming
Returns the solution.
getSolveMethod() - Method in class com.imsl.math.OdeAdamsGear
Returns the method for solving the formula equations.
getSpline() - Method in class com.imsl.math.BSpline
Returns a Spline representation of the B-spline.
getSplineCoefficients() - Method in class com.imsl.math.FeynmanKac
Returns the coefficients of the Hermite quintic splines that represent an approximate solution of the Feynman-Kac PDE.
getSplineCoefficientsPrime() - Method in class com.imsl.math.FeynmanKac
Returns the first derivatives of the Hermite quintic spline coefficients that represent an approximate solution of the Feynman-Kac PDE.
getSplineValue(double[], double[], int) - Method in class com.imsl.math.FeynmanKac
Evaluates for time value 0 or a time value in tGrid the derivative of the Hermite quintic spline interpolant at evaluation points within the range of xGrid.
getSpread() - Method in class com.imsl.datamining.neural.ScaleFilter
Retrieves the measure of spread to be used during scaling.
getSSE() - Method in class com.imsl.stat.NonlinearRegression
Returns the sums of squares for error.
getSSResidual() - Method in class com.imsl.stat.ARMA
Returns the sum of squares of the random shock.
getStage1Trainer() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the stage 1 trainer.
getStage2Trainer() - Method in class com.imsl.datamining.neural.EpochTrainer
Returns the stage 1 trainer.
getStandardDeviation() - Method in class com.imsl.stat.LogNormalDistribution
Returns the lognormal probability distribution standard deviation parameter.
getStandardDeviation() - Method in class com.imsl.stat.NormalDistribution
Returns the population standard deviation.
getStandardDeviation() - Method in class com.imsl.stat.Summary
Returns the population standard deviation.
getStandardDeviations(double[][], int[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns a table of standard deviations for each continuous attribute in continuousData segmented by the target classes in classificationData.
getStandardError(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests
Returns the estimated standard error for a coefficient estimate.
getStandardError(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests
Returns the estimated standard error for a coefficient estimate.
getStandardErrors(int) - Method in class com.imsl.stat.AutoCorrelation
Returns the standard errors of the autocorrelations of the time series x.
getStandardErrors(int) - Method in class com.imsl.stat.CrossCorrelation
Returns the standard errors of the cross-correlations between the time series x and y.
getStandardErrors() - Method in class com.imsl.stat.FactorAnalysis
Returns the estimated asymptotic standard errors of the eigenvalues.
getStandardErrors() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns Greenwood's estimated standard errors.
getStandardizedResidual() - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Returns the Standardized Residual for an observation.
getStatement() - Method in class com.imsl.io.AbstractFlatFile
Returns the Statement object that produced this ResultSet object.
getStateVector() - Method in class com.imsl.stat.KalmanFilter
Returns the estimated state vector at time k + 1 given the observations through time k.
getStatistics() - Method in class com.imsl.chart.BoxPlot
Returns an array of BoxPlot.Statistics objects, one for each set of observations.
getStatistics(int) - Method in class com.imsl.chart.BoxPlot
Returns a BoxPlot.Statistics for a set of observations.
getStatistics() - Method in class com.imsl.stat.ContingencyTable
Returns the statistics associated with this table.
getStatistics() - Method in class com.imsl.stat.DiscriminantAnalysis
Returns statistics.
getStatistics() - Method in class com.imsl.stat.FactorAnalysis
Returns statistics.
getStatistics() - Method in class com.imsl.stat.SelectionRegression
Returns a new Statistics object.
getStatistics() - Method in class com.imsl.stat.WilcoxonRankSum
Returns the statistics.
getStatus() - Method in class com.imsl.math.NumericalDerivatives
Returns status information.
getStatus(int) - Method in class com.imsl.math.ZeroPolynomial
Returns the error status of a root.
getStdDev() - Method in class com.imsl.stat.NormOneSample
Returns the standard deviation of the sample.
getStdDevX() - Method in class com.imsl.stat.NormTwoSample
Returns the standard deviation of the first sample.
getStdDevY() - Method in class com.imsl.stat.NormTwoSample
Returns the standard deviation of the second sample.
getStepControlMethod() - Method in class com.imsl.math.FeynmanKac
Returns the step control method used in the integration of the Feynman-Kac PDE.
getStratumColumn() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the column index of x containing the stratum number for each observation.
getStratumColumn() - Method in class com.imsl.stat.ProportionalHazards
Returns the column index of x containing the stratum number for each observation.
getStratumNumbers() - Method in class com.imsl.stat.ProportionalHazards
Returns the stratum number used for each observation.
getStratumRatio() - Method in class com.imsl.stat.ProportionalHazards
Returns the ratio at which a stratum is split into two strata.
getString() - Method in class com.imsl.chart.Text
Gets the string for this Text object.
getString(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a String in the Java programming language.
getString(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a String in the Java programming language.
getStringAttribute(String) - Method in class com.imsl.chart.AbstractChartNode
Convenience routine to get a String-valued attribute.
getSumOfSquares() - Method in class com.imsl.stat.KalmanFilter
Returns the generalized sum of squares.
getSumOfSquaresForError() - Method in class com.imsl.stat.ANOVA
Returns the sum of squares for error.
getSumOfSquaresForModel() - Method in class com.imsl.stat.ANOVA
Returns the sum of squares for model.
getSumOfWeights() - Method in class com.imsl.stat.Covariances
Returns the sum of the weights of all observations.
getSurfaceType() - Method in class com.imsl.chart3d.Surface
Returns the attribute "SurfaceType".
getSurvivalProbabilities() - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the estimated survival probabilities.
getSwept() - Method in class com.imsl.stat.StepwiseRegression
Returns an array containing information indicating whether or not a particular variable is in the model.
getSymbolicFactor() - Method in class com.imsl.math.ComplexSparseCholesky
Returns the symbolic Cholesky factor.
getSymbolicFactor() - Method in class com.imsl.math.SparseCholesky
Returns the symbolic Cholesky factor.
getSymmetricMode() - Method in class com.imsl.math.ComplexSuperLU
Returns the symmetric mode flag.
getSymmetricMode() - Method in class com.imsl.math.SuperLU
Returns the symmetric mode flag.
getTable() - Method in class com.imsl.stat.TableMultiWay.BalancedTable
Returns an array containing the frequencies for each variable.
getTable() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable
Returns the frequency for each cell.
getTauStatistics() - Method in class com.imsl.stat.ARMAOutlierIdentification
Returns the t value for each detected outlier.
getTerminationCriterion() - Method in class com.imsl.math.MinConNLP
Returns the reason the solve step terminated.
getTestEffects() - Method in class com.imsl.stat.ANOVAFactorial
Returns statistics relating to the sums of squares for the effects in the model.
getTestStatistic() - Method in class com.imsl.stat.KolmogorovOneSample
Returns D = max(D^{+}, D^{-}).
getTestStatistic() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns D = max(D^{+}, D^{-}).
getText() - Method in class com.imsl.chart.Annotation
Gets the Text for this Annotation object.
getTextAngle() - Method in class com.imsl.chart.ChartNode
Returns the value of the "TextAngle" attribute.
getTextColor() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "TextColor" attribute.
getTextColor() - Method in class com.imsl.chart.ChartNode
Returns the value of the "TextColor" attribute.
getTextFormat() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "TextFormat" attribute.
getTheta() - Method in class com.imsl.stat.PoissonDistribution
Returns the mean number of successes in a given time period of the Poisson probability distribution.
getTickInterval() - Method in class com.imsl.chart.Axis1D
Retrieves the tick interval.
getTickInterval() - Method in class com.imsl.chart.AxisR
Retrieves the tick interval.
getTickInterval() - Method in class com.imsl.chart3d.Axis3D
Retrieves the tick interval.
getTickLength() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "TickLength" attribute.
getTicks() - Method in class com.imsl.chart.Axis1D
Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart.AxisR
Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart.AxisTheta
Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart3d.Axis3D
Returns the value of the "Ticks" attribute, if set.
getTicks() - Method in class com.imsl.chart3d.ColormapLegend
Returns the value of the "Ticks" attribute, if set.
getTiesOption() - Method in class com.imsl.stat.ProportionalHazards
Returns the method used for handling ties.
getTime(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTime(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTime(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTime(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Time object in the Java programming language.
getTimeBarrier() - Method in class com.imsl.math.FeynmanKac
Returns the barrier set for integration in the time direction.
getTimes() - Method in class com.imsl.stat.KaplanMeierECDF
Retrieves the time values where the step function CDF jumps to a greater value.
getTimeSeries() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the time series used for estimating the minimum AIC and the autoregressive coefficients.
getTimeSeries() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the time series used to construct ARMAMaxLikelihood.
getTimeSeries() - Method in class com.imsl.stat.ARSeasonalFit
Returns the time series.
getTimestamp(int) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.
getTimestamp(String) - Method in class com.imsl.io.AbstractFlatFile
Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object.
getTimestamp(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.
getTimestamp(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile
Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Timestamp object in the Java programming language.
getTimsacAR() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final auto regressive parameter estimates at the optimum AIC estimated by the original TIMSAC routine (UNIMAR).
getTimsacConstant() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the estimate for the constant parameter in the ARMA series.
getTimsacVariance() - Method in class com.imsl.stat.ARAutoUnivariate
Returns the final estimate for the innovation variance calculated by the TIMSAC automatic AR modeling routine (UNIMAR).
getTitle() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Title" attribute.
getTitle() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Title" attribute.
getTo() - Method in class com.imsl.datamining.neural.Link
Returns the destination Node for this Link.
getTolerance() - Method in class com.imsl.chart.DrawMap
Get the minimum distance that an event can be from a point or a line and still be considered a hit.
getTolerance() - Method in class com.imsl.chart.DrawPick
Get the minimum distance that an event can be from a point or a line and still be considered a hit.
getTolerance() - Method in class com.imsl.math.MinConNLP
Returns the desired precision of the solution.
getTolerance() - Method in class com.imsl.math.ODE
Returns the error tolerance.
getTolerance() - Method in class com.imsl.stat.ARMAMaxLikelihood
Returns the tolerance for the convergence algorithm.
getToolTip() - Method in class com.imsl.chart.ChartNode
Returns the value of the "ToolTip" attribute.
getTotalDegreesOfFreedom() - Method in class com.imsl.stat.ANOVA
Returns the total degrees of freedom.
getTotalMissing() - Method in class com.imsl.stat.ANOVA
Returns the total number of missing values.
getTotalMissing() - Method in class com.imsl.stat.EmpiricalQuantiles
Returns the total number of missing values.
getTotalNumberOfFailures(double) - Method in class com.imsl.stat.KaplanMeierEstimates
Returns the total number failing in the group for the specified group value.
getTotalSumOfSquares() - Method in class com.imsl.stat.ANOVA
Returns the total sum of squares.
getTrainingErrors() - Method in class com.imsl.datamining.NaiveBayesClassifier
Returns a table of classification errors of non-missing classifications for each target classification plus the overall total of classification errors.
getTrainingIterations() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the number of iterations used during training.
getTransform() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Transform" attribute.
getTransform() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Retrieves the transform flag used for encoding and decoding.
getTransformedTimeSeries() - Method in class com.imsl.stat.ARSeasonalFit
Returns the transformed series, W_t(s,d).
getTransformType() - Method in class com.imsl.stat.ClusterHierarchical
Returns the type of transformation.
getTreemapLegend() - Method in class com.imsl.chart.Treemap
Returns the treemap legend.
getTStatistic(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests
Returns the t-statistic for the test that the i-th coefficient is zero.
getTStatistic(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests
Returns the student-t test statistic for testing the i-th coefficient equal to zero ({beta}_{index} = 0).
getTTest() - Method in class com.imsl.stat.NormOneSample
Returns the test statistic associated with the t test.
getTTest() - Method in class com.imsl.stat.NormTwoSample
Returns the test statistic for the Satterthwaite's approximation.
getTTestDF() - Method in class com.imsl.stat.NormOneSample
Returns the degrees of freedom associated with the t test for the mean.
getTTestDF() - Method in class com.imsl.stat.NormTwoSample
Returns the degrees of freedom for the Satterthwaite's approximation for t-test for either equal or unequal variances, depending on the value set by setUnequalVariances.
getTTestP() - Method in class com.imsl.stat.NormOneSample
Returns the probability associated with the t test of a larger t in absolute value.
getTTestP() - Method in class com.imsl.stat.NormTwoSample
Returns the approximate probability of a larger t for the Satterthwaite's approximation for equal or unequal variances.
getTukeyScores(double[]) - Method in class com.imsl.stat.Ranks
Gets the Tukey version of normal scores for each observation.
getTwoSidedPValue() - Method in class com.imsl.stat.KolmogorovOneSample
Probability of the statistic exceeding D under the null hypothesis of equality and against the two-sided alternative.
getTwoSidedPValue() - Method in class com.imsl.stat.KolmogorovTwoSample
Probability of the statistic exceeding D under the null hypothesis of equality and against the two-sided alternative.
getType() - Method in class com.imsl.chart.Axis1D
Returns the axis type.
getType() - Method in class com.imsl.chart.Grid
Returns the axis type.
getType() - Method in class com.imsl.chart3d.Axis3D
Returns the axis type.
getType() - Method in class com.imsl.io.AbstractFlatFile
Returns the type of this ResultSet object.
getTypeVariable(int) - Method in class com.imsl.io.MPSReader
Returns the type of a variable.
getU() - Method in class com.imsl.math.ComplexLU
Returns the unit upper triangular portion of the LU factorization of A.
getU() - Method in class com.imsl.math.LU
Returns the unit upper triangular portion of the LU factorization of A.
getU() - Method in class com.imsl.math.SVD
Returns the left singular vectors.
getUnbalancedTable() - Method in class com.imsl.stat.TableMultiWay
Returns an object containing the unbalanced table.
getUp() - Method in class com.imsl.chart.Candlestick
Returns the CandlestickItem for up days.
getUpperAdjacentValue() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the lower adjacent value.
getUpperBound(int) - Method in class com.imsl.io.MPSReader
Returns the upper bound for a variable.
getUpperCICommonVariance() - Method in class com.imsl.stat.NormTwoSample
Returns the upper confidence limits for the common, or pooled, variance.
getUpperCIDiff() - Method in class com.imsl.stat.NormTwoSample
Returns the upper confidence limit for the mean of the first population minus the mean of the second for equal or unequal variances depending on the value set by setUnequalVariances.
getUpperCIMean() - Method in class com.imsl.stat.NormOneSample
Returns the upper confidence limit for the mean.
getUpperCIRatioVariance() - Method in class com.imsl.stat.NormTwoSample
Returns the approximate upper confidence limit for the ratio of the variance of the first population to the second.
getUpperCIVariance() - Method in class com.imsl.stat.NormOneSample
Returns the upper confidence limits for the variance.
getUpperControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart
Returns the upper control limit.
getUpperQuartile() - Method in class com.imsl.chart.BoxPlot.Statistics
Returns the upper quartile value.
getUpperRange(int) - Method in class com.imsl.io.MPSReader
Returns the upper range value for a constraint equation.
getURL(String) - Method in class com.imsl.io.AbstractFlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a java.net.URL object.
getURL(int) - Method in class com.imsl.io.AbstractFlatFile
Retrieves the value of the designated column in the current row of this ResultSet object as a java.net.URL object.
getUseBackPropagation() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Returns the use back propagation setting.
getV() - Method in class com.imsl.math.SVD
Returns the right singular vectors.
getValue() - Method in class com.imsl.chart.qc.ControlLimit
Returns the value of this control limit line.
getValue() - Method in class com.imsl.datamining.neural.InputNode
Returns the value of this node.
getValue() - Method in class com.imsl.datamining.neural.OutputPerceptron
Returns the value of the OutputPerceptron determined using the current network state and inputs.
getValue() - Method in class com.imsl.io.MPSReader.Element
Returns the value of the element.
getValues() - Method in class com.imsl.math.Eigen
Returns the eigenvalues of a matrix of type double.
getValues() - Method in class com.imsl.math.SymEigen
Returns the eigenvalues
getValues() - Method in class com.imsl.stat.FactorAnalysis
Returns the eigenvalues.
getValues() - Method in class com.imsl.stat.TableMultiWay.BalancedTable
Returns the values of the classification variables.
getVanDerWaerdenScores(double[]) - Method in class com.imsl.stat.Ranks
Gets the Van der Waerden version of normal scores for each observation.
getVarCovAdjustedMeans() - Method in class com.imsl.stat.ANCOVA
Returns a matrix containing the estimated variances and covariances for the adjusted means assuming parallelism.
getVarCovarMatrix() - Method in class com.imsl.stat.GARCH
Returns the variance-covariance matrix.
getVarCovCoefficients() - Method in class com.imsl.stat.ANCOVA
Returns a matrix containing the estimated variances and covariances for the coefficients returned using getModelCoefficients.
getVariance() - Method in class com.imsl.stat.ARMA
Returns the variance of the time series z.
getVariance() - Method in class com.imsl.stat.AutoCorrelation
Returns the variance of the time series x.
getVariance() - Method in class com.imsl.stat.Summary
Returns the population variance.
getVarianceCovarianceMatrix() - Method in class com.imsl.stat.ProportionalHazards
Returns the estimated asymptotic variance-covariance matrix of the parameters.
getVariances() - Method in class com.imsl.stat.FactorAnalysis
Gets the unique variances.
getVarianceX() - Method in class com.imsl.stat.CrossCorrelation
Returns the variance of time series x.
getVarianceX() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the variances of the channels of x.
getVarianceY() - Method in class com.imsl.stat.CrossCorrelation
Returns the variance of time series y.
getVarianceY() - Method in class com.imsl.stat.MultiCrossCorrelation
Returns the variances of the channels of y.
getVectorProducts() - Method in class com.imsl.math.GenMinRes
Returns the user-supplied functions for the inner product and, optionally, the norm used in the Gram-Schmidt implementations.
getVectors() - Method in class com.imsl.math.Eigen
Returns the eigenvectors.
getVectors() - Method in class com.imsl.math.SymEigen
Return the eigenvectors of a symmetric matrix of type double.
getVectors() - Method in class com.imsl.stat.FactorAnalysis
Returns the eigenvectors.
getViewPlatformTransformation(Transform3D) - Method in class com.imsl.chart3d.Chart3D
Sets the transformation for the view platform.
getViewport() - Method in class com.imsl.chart.ChartNode
Returns the value of the "Viewport" attribute.
getViewport() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Viewport" attribute.
getVirtualUniverse() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Universe" attribute.
getVisibleFaces() - Method in class com.imsl.chart3d.AxisBox
Returns the flag indicating which faces of the box are to be drawn.
getWarning() - Static method in class com.imsl.Warning
Gets the WarningObject.
getWarnings() - Method in class com.imsl.io.AbstractFlatFile
Returns the first warning reported by calls on this ResultSet object.
getWbar() - Method in class com.imsl.chart.qc.XbarS
Returns the value of the "Wbar" attribute, the within sample variation for a series of samples.
getWeight() - Method in class com.imsl.datamining.neural.Link
Returns the weight for this Link.
getWeights() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Returns the weights for the Links in this network.
getWeights() - Method in class com.imsl.datamining.neural.Network
Returns the weights.
getWhiskers() - Method in class com.imsl.chart.BoxPlot
Returns the Whiskers node.
getWindow() - Method in class com.imsl.chart.Axis1D
Returns the window for an Axis1D.
getWindow() - Method in class com.imsl.chart.AxisR
Returns the Window attribute.
getWindow() - Method in class com.imsl.chart.AxisTheta
Returns the window for an AxisTheta.
getWindow() - Method in class com.imsl.chart3d.Axis3D
Returns the window for an Axis1D.
getWindow() - Method in class com.imsl.chart3d.ColormapLegend
Returns the window for a ColormapLegend.
getX() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "X" attribute.
getX() - Method in class com.imsl.stat.GARCH
Returns the estimated parameter array, x.
getXHi() - Method in class com.imsl.stat.EmpiricalQuantiles
Returns the smallest element of x greater than or equal to the desired quantile.
getXKnots() - Method in class com.imsl.math.Spline2D
Returns the knot sequences in the x-direction.
getXLo() - Method in class com.imsl.stat.EmpiricalQuantiles
Returns the largest element of x less than or equal to the desired quantile.
getXOrder() - Method in class com.imsl.math.Spline2DLeastSquares
Returns the order of the spline in the x-direction.
getXWeights() - Method in class com.imsl.math.Spline2DLeastSquares
Returns the weights for the least-squares fit in the x-direction.
getY() - Method in class com.imsl.chart.AbstractChartNode
Returns the value of the "Y" attribute.
getYearBasis() - Method in class com.imsl.finance.DayCountBasis
Returns the (days in year) portion of the Day Count Basis.
getYKnots() - Method in class com.imsl.math.Spline2D
Returns the knot sequences in the y-direction.
getYOrder() - Method in class com.imsl.math.Spline2DLeastSquares
Returns the order of the spline in the y-direction.
getYWeights() - Method in class com.imsl.math.Spline2DLeastSquares
Returns the weights for the least-squares fit in the y-direction.
getZ() - Method in class com.imsl.chart3d.ChartNode3D
Returns the value of the "Z" attribute.
getZ() - Method in class com.imsl.stat.KolmogorovOneSample
Returns the normalized D statistic without the continuity correction applied.
getZ() - Method in class com.imsl.stat.KolmogorovTwoSample
Returns the normalized D statistic without the continuity correction applied.
go_to(int) - Static method in class com.imsl.Dummy
 
gradient(double[], double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockGradObjective
 
gradient(double[], double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.GradObjective
 
gradient(double[], double[]) - Method in interface com.imsl.math.MinConGenLin.Gradient
Public interface for the user-supplied function to compute the gradient at point x.
gradient(double[], int, double[]) - Method in interface com.imsl.math.MinConNLP.Gradient
Computes the value of the gradient of the function at the given point.
gradient(double[], double[]) - Method in interface com.imsl.math.MinUnconMultiVar.Gradient
Public interface for the gradient of the multivariate function to be minimized.
gradient(double[]) - Method in class com.imsl.math.RadialBasis
Returns the gradient of the radial basis approximation at a point.
graphics - Variable in class com.imsl.chart.Draw
 
GREEN - Static variable in interface com.imsl.chart.Colormap
Linear green colormap.
GREEN_PINK - Static variable in interface com.imsl.chart.Colormap
Green/pink colormap.
GREEN_RED_BLUE_WHITE - Static variable in interface com.imsl.chart.Colormap
Green/red/blue/white colormap.
GREEN_WHITE_EXPONENTIAL - Static variable in interface com.imsl.chart.Colormap
Exponential green/white colormap.
GREEN_WHITE_LINEAR - Static variable in interface com.imsl.chart.Colormap
Linear green/white colormap.
Grid - Class in com.imsl.chart
Draws the grid lines perpendicular to an axis.
GridPolar - Class in com.imsl.chart
Draws the grid lines for a polar plot.

H

hashCode() - Method in class com.imsl.math.Complex
Returns a hashcode for this Complex.
hasMoreTokens() - Method in class com.imsl.io.Tokenizer
Returns true if a call to nextToken will not generate an exception.
haveErrorBarProperties - Variable in class com.imsl.chart.Draw
 
haveFillProperties - Variable in class com.imsl.chart.Draw
 
haveImageProperties - Variable in class com.imsl.chart.Draw
 
haveLineProperties - Variable in class com.imsl.chart.Draw
 
haveMarkerProperties - Variable in class com.imsl.chart.Draw
 
haveTextProperties - Variable in class com.imsl.chart.Draw
 
Heatmap - Class in com.imsl.chart
Heatmap creates a chart from a two-dimensional array of double precision values or Color values.
Heatmap(AxisXY, double, double, double, double, Color[][]) - Constructor for class com.imsl.chart.Heatmap
Creates a Heatmap from an array of Color values.
Heatmap(AxisXY, double, double, double, double, double, double, double[][], Colormap) - Constructor for class com.imsl.chart.Heatmap
Creates a Heatmap from an array of double values and a Colormap.
Heatmap.Legend - Class in com.imsl.chart
A legend for use with a heatmap.
hessian(double[], double[][]) - Method in interface com.imsl.math.MinUnconMultiVar.Hessian
Public interface for the Hessian of the multivariate function to be minimized.
HiddenLayer - Class in com.imsl.datamining.neural
Hidden layer in a neural network.
HighLowClose - Class in com.imsl.chart
High-low-close plot of stock data.
HighLowClose(AxisXY, Date, double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose
Constructs a high-low-close chart node beginning with specified start date.
HighLowClose(AxisXY, Date, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose
Constructs a high-low-close-open chart node beginning with specified start date.
HighLowClose(AxisXY, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose
Constructs a high-low-close chart node at specified axis points.
HighLowClose(AxisXY, double[], double[], double[], double[], double[]) - Constructor for class com.imsl.chart.HighLowClose
Constructs a high-low-close-open chart node at specified axis points.
horizontalStripe(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a horizontally striped pattern.
Hyperbolic - Class in com.imsl.math
Pure Java implementation of the hyperbolic functions and their inverses.
hypergeometric(int, int, int, int) - Static method in class com.imsl.stat.Cdf
Evaluates the hypergeometric cumulative probability distribution function.
hypergeometric(int, int, int, int) - Static method in class com.imsl.stat.Pdf
Evaluates the hypergeometric probability density function.
HyperRectangleQuadrature - Class in com.imsl.math
HyperRectangleQuadrature integrates a function over a hypercube.
HyperRectangleQuadrature(int) - Constructor for class com.imsl.math.HyperRectangleQuadrature
Constructs a HyperRectangleQuadrature object.
HyperRectangleQuadrature(RandomSequence) - Constructor for class com.imsl.math.HyperRectangleQuadrature
Constructs a HyperRectangleQuadrature object.
HyperRectangleQuadrature.Function - Interface in com.imsl.math
Public interface function for the HyperRectangleQuadrature class.

I

I(double, int) - Static method in class com.imsl.math.Bessel
Evaluates a sequence of modified Bessel functions of the first kind with integer order and real argument.
I(double, double, int) - Static method in class com.imsl.math.Bessel
Evaluates a sequence of modified Bessel functions of the first kind with real order and real argument.
i - Static variable in class com.imsl.math.Complex
The imaginary unit.
IEEE - Class in com.imsl.math
Pure Java implementation of the IEEE 754 functions as specified in IEEE Standard for Binary Floating-Point Arithmetic, ANSI/IEEE Standard 754-1985 (IEEE, New York).
IEEEremainder(double, double) - Static method in class com.imsl.math.JMath
Returns the IEEE remainder from x divided by p.
ignoreMissingValues(boolean) - Method in class com.imsl.datamining.NaiveBayesClassifier
Specifies whether or not missing values will be ignored during the training process.
ilogb(double) - Static method in class com.imsl.math.IEEE
Return the binary exponent of non-zero x.
imag() - Method in class com.imsl.math.Complex
Returns the imaginary part of a Complex object.
imag(Complex) - Static method in class com.imsl.math.Complex
Returns the imaginary part of a Complex object.
IMAGE - Static variable in class com.imsl.chart.Draw
 
image(ImageIcon) - Static method in class com.imsl.chart.FillPaint
Returns a tiling of an image.
IMAGE_FACTOR_ANALYSIS - Static variable in class com.imsl.stat.FactorAnalysis
Indicates image factor analysis.
imageObserver - Variable in class com.imsl.chart.Draw
 
IMSLException - Exception in com.imsl
Signals that a mathematical exception has occurred.
IMSLException() - Constructor for exception com.imsl.IMSLException
Constructs an IMSLException with no detail message.
IMSLException(String) - Constructor for exception com.imsl.IMSLException
Constructs an IMSLException with the specified detail message.
IMSLException(String, String, Object[]) - Constructor for exception com.imsl.IMSLException
Constructs an IMSLException with the specified detail message.
IMSLFormatter - Class in com.imsl
Simple formatter for classes that implement logging.
IMSLFormatter() - Constructor for class com.imsl.IMSLFormatter
 
IMSLRuntimeException - Exception in com.imsl
Signals that an error has occurred.
IMSLRuntimeException() - Constructor for exception com.imsl.IMSLRuntimeException
Constructs an IMSLRuntimeException with no detail message.
IMSLRuntimeException(String) - Constructor for exception com.imsl.IMSLRuntimeException
Constructs an IMSLRuntimeException with the specified detail message.
IMSLRuntimeException(String, String, Object[]) - Constructor for exception com.imsl.IMSLRuntimeException
Constructs an IMSLRuntimeException with the specified detail message.
IMSLUnexpectedErrorException - Exception in com.imsl
Signals that an unexpected error has occurred.
IMSLUnexpectedErrorException() - Constructor for exception com.imsl.IMSLUnexpectedErrorException
Constructs an IMSLUnexpectedErrorException.
incrementEpochCount() - Method in class com.imsl.datamining.neural.EpochTrainer
Increments the epoch counter.
index - Variable in class com.imsl.math.ComplexSparseMatrix.SparseArray
Jagged array containing column indices.
index - Variable in class com.imsl.math.SparseMatrix.SparseArray
Jagged array containing column indices.
INFINITY_NORM - Static variable in class com.imsl.stat.Dissimilarities
Indicates the maximum difference (L_infty norm) distance method.
infinityNorm(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Return the infinity norm of a Complex matrix.
infinityNorm() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the infinity norm of the matrix.
infinityNorm(double[][]) - Static method in class com.imsl.math.Matrix
Return the infinity norm of a matrix.
infinityNorm() - Method in class com.imsl.math.SparseMatrix
Returns the infinity norm of the matrix.
init() - Method in class com.imsl.chart.ChartServlet
 
init(double[], double[], double, double[], double[], double[], double[]) - Method in interface com.imsl.math.FeynmanKac.InitialData
Method that allows for adjustment of initial data or as an opportunity for output during the integration steps.
innerproduct(double[], double[]) - Method in interface com.imsl.math.GenMinRes.VectorProducts
Used to compute the inner product of 2 vectors for the Gram-Schmidt implementation.
INNOVATIONAL - Static variable in class com.imsl.stat.ARMAOutlierIdentification
Indicates detection of an innovational outlier.
INNOVATIONAL - Static variable in class com.imsl.stat.AutoARIMA
Indicates detection of an innovational outlier.
InputLayer - Class in com.imsl.datamining.neural
Input layer in a neural network.
InputNode - Class in com.imsl.datamining.neural
A Node in the InputLayer.
insertRow() - Method in class com.imsl.io.AbstractFlatFile
Inserts the contents of the insert row into this ResultSet object and into the database.
INTEGER_VARIABLE - Static variable in class com.imsl.io.MPSReader
Variable must be an integer.
integral(double, double) - Method in class com.imsl.math.BSpline
Returns the value of an integral of the B-spline.
integral(double, double) - Method in class com.imsl.math.Spline
Returns the value of an integral of the spline.
integral(double, double, double, double) - Method in class com.imsl.math.Spline2D
Returns the value of an integral of a tensor-product spline on a rectangular domain.
intrate(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the interest rate of a fully invested security.
intValue() - Method in class com.imsl.math.Complex
Returns the value of the real part as an int.
intValue() - Method in class com.imsl.math.Physical
Returns the value of this dimensionless object.
InvCdf - Class in com.imsl.stat
Inverse cumulative probability distribution functions.
inverse() - Method in class com.imsl.math.Cholesky
Returns the inverse of this matrix
inverse() - Method in class com.imsl.math.ComplexLU
Returns the inverse of the matrix used to construct this instance.
inverse() - Method in class com.imsl.math.LU
Returns the inverse of the matrix used to construct this instance.
inverse() - Method in class com.imsl.math.SVD
Compute the Moore-Penrose generalized inverse of a real matrix.
InverseCdf - Class in com.imsl.stat
Inverse of user-supplied cumulative distribution function.
InverseCdf(CdfFunction) - Constructor for class com.imsl.stat.InverseCdf
Constructor for the inverse of a user-supplied cummulative distribution function.
InverseCdf.DidNotConvergeException - Exception in com.imsl.stat
The iteration did not converge
InverseCdf.DidNotConvergeException(String) - Constructor for exception com.imsl.stat.InverseCdf.DidNotConvergeException
 
InverseCdf.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.stat.InverseCdf.DidNotConvergeException
 
inverseLowerTriangular(double[][]) - Static method in class com.imsl.math.Matrix
Returns the inverse of the lower triangular matrix a.
inverseUpperTriangular(double[][]) - Static method in class com.imsl.math.Matrix
Returns the inverse of the upper triangular matrix a.
ipmt(double, int, int, double, double, int) - Static method in class com.imsl.finance.Finance
Returns the interest payment for an investment for a given period.
ipvt - Variable in class com.imsl.math.ComplexLU
Vector of length n containing the pivot sequence for the factorization.
ipvt - Variable in class com.imsl.math.LU
Vector of length n containing the pivot sequence for the factorization.
irr(double[]) - Static method in class com.imsl.finance.Finance
Returns the internal rate of return for a schedule of cash flows.
irr(double[], double) - Static method in class com.imsl.finance.Finance
Returns the internal rate of return for a schedule of cash flows.
isAfterLast() - Method in class com.imsl.io.AbstractFlatFile
Indicates whether the cursor is after the last row in this ResultSet object.
isAncestorOf(AbstractChartNode) - Method in class com.imsl.chart.AbstractChartNode
Returns true if this node is an ancestor of the argument node.
isAttributeSet(String) - Method in class com.imsl.chart.AbstractChartNode
Determines if an attribute is defined (may have been inherited).
isAttributeSetAtThisNode(String) - Method in class com.imsl.chart.AbstractChartNode
Determines if an attribute is defined in this node (not inherited).
isBeforeFirst() - Method in class com.imsl.io.AbstractFlatFile
Indicates whether the cursor is before the first row in this ResultSet object.
isBitSet(int, int) - Static method in class com.imsl.chart.AbstractChartNode
Returns true if the bit set in flag is set in mask.
isBitSet(int, int) - Static method in class com.imsl.chart.ChartNode
Returns true if the bit set in flag is set in mask.
isFirst() - Method in class com.imsl.io.AbstractFlatFile
Indicates whether the cursor is on the first row of this ResultSet object.
isInvertible(double[]) - Method in class com.imsl.stat.ARMAMaxLikelihood
Tests whether the coefficients in ma are invertible
isLast() - Method in class com.imsl.io.AbstractFlatFile
Indicates whether the cursor is on the last row of this ResultSet object.
isNaN(double) - Static method in class com.imsl.math.IEEE
NaN test on an argument of type double.
isNoMoreProgress() - Method in class com.imsl.math.QuadraticProgramming
Returns true if due to computer rounding error, a change in the variables fail to improve the objective function.
isProportionalWidth() - Method in class com.imsl.chart.BoxPlot
Returns the value of the attribute "ProportionalWidth".
isStationary(double[]) - Method in class com.imsl.stat.ARMAMaxLikelihood
Tests whether the coefficients in ar are stationary.
isWeekday(GregorianCalendar) - Method in class com.imsl.chart.TransformDate
Returns true if the specified date is a weekday.
iterator() - Method in class com.imsl.io.MPSReader.Row
Returns an iterator over the elements in this row.

J

J(double, int) - Static method in class com.imsl.math.Bessel
Evaluates a sequence of Bessel functions of the first kind with integer order and real argument.
J(double, double, int) - Static method in class com.imsl.math.Bessel
Evaluate a sequence of Bessel functions of the first kind with real order and real positive argument.
jacobian(double[], double[][]) - Method in interface com.imsl.math.NonlinLeastSquares.Jacobian
Public interface for the nonlinear least squares function.
jacobian(double[]) - Method in interface com.imsl.math.NumericalDerivatives.Jacobian
User-supplied function to compute the Jacobian.
jacobian(double, double[], double[]) - Method in interface com.imsl.math.OdeAdamsGear.Jacobian
Used to compute the Jacobian of the function at t.
jacobian(double[], double[][]) - Method in interface com.imsl.math.ZeroSystem.Jacobian
Returns the value of the Jacobian at the given point.
JFrameChart - Class in com.imsl.chart
JFrameChart is a JFrame that contains a chart.
JFrameChart() - Constructor for class com.imsl.chart.JFrameChart
Creates new JFrameChart to display a chart.
JFrameChart(Chart) - Constructor for class com.imsl.chart.JFrameChart
Creates new JFrameChart to display a given chart.
JFrameChart3D - Class in com.imsl.chart3d
JFrameChart3D is a JFrame that contains a chart.
JFrameChart3D() - Constructor for class com.imsl.chart3d.JFrameChart3D
Creates new JFrameChart3D to display a chart.
JFrameChart3D(Chart3D) - Constructor for class com.imsl.chart3d.JFrameChart3D
Creates new JFrameChart3D to display a given chart.
JMath - Class in com.imsl.math
Pure Java implementation of the standard java.lang.Math class.
JPanelChart - Class in com.imsl.chart
A Swing JPanel that contains a chart.
JPanelChart() - Constructor for class com.imsl.chart.JPanelChart
Creates new JPanelChart.
JPanelChart(Chart) - Constructor for class com.imsl.chart.JPanelChart
Creates new JPanelChart using a given Chart object.
JspBean - Class in com.imsl.chart
JspBean is used to refer to charts in a Java Server Page that are later rendered using the ChartServlet.
JspBean() - Constructor for class com.imsl.chart.JspBean
Creates a JspBean object.

K

K(double, int) - Static method in class com.imsl.math.Bessel
Evaluates a sequence of modified Bessel functions of the third kind with integer order and real argument.
K(double, double, int) - Static method in class com.imsl.math.Bessel
Evaluates a sequence of modified Bessel functions of the third kind with fractional order and real argument.
KalmanFilter - Class in com.imsl.stat
Performs Kalman filtering and evaluates the likelihood function for the state-space model.
KalmanFilter(double[], double[][], int, double, double) - Constructor for class com.imsl.stat.KalmanFilter
Constructor for KalmanFilter.
KaplanMeierECDF - Class in com.imsl.stat
Computes the Kaplan-Meier reliability function estimates or the CDF based on failure data that may be multi-censored.
KaplanMeierECDF(double[]) - Constructor for class com.imsl.stat.KaplanMeierECDF
Constructor for KaplanMeierECDF.
KaplanMeierEstimates - Class in com.imsl.stat
Computes Kaplan-Meier (or product-limit) estimates of survival probabilities for a sample of failure times that possibly contain right consoring.
KaplanMeierEstimates(double[][]) - Constructor for class com.imsl.stat.KaplanMeierEstimates
Constructor for KaplanMeierEstimates.
kappa(double, double) - Method in interface com.imsl.math.FeynmanKac.PdeCoefficients
Returns the value of the kappa coefficient at the given point.
keySet() - Method in class com.imsl.chart.xml.ChartXML
Returns the Set view of all id's defined in the XML file.
knot - Variable in class com.imsl.math.BSpline
The knot array of length n + order, where n is the number of coefficients in the B-spline.
KolmogorovOneSample - Class in com.imsl.stat
The class KolmogorovOneSample performs a Kolmogorov-Smirnov goodness-of-fit test in one sample.
KolmogorovOneSample(CdfFunction, double[]) - Constructor for class com.imsl.stat.KolmogorovOneSample
Constructs a one sample Kolmogorov-Smirnov goodness-of-fit test.
KolmogorovTwoSample - Class in com.imsl.stat
Performs a Kolmogorov-Smirnov two-sample test.
KolmogorovTwoSample(double[], double[]) - Constructor for class com.imsl.stat.KolmogorovTwoSample
Constructs a two sample Kolmogorov-Smirnov goodness-of-fit test.
kurtosis(double[]) - Static method in class com.imsl.stat.Summary
Returns the kurtosis of the given data set.
kurtosis(double[], double[]) - Static method in class com.imsl.stat.Summary
Returns the kurtosis of the given data set and associated weights.

L

L1_NORM - Static variable in class com.imsl.stat.Dissimilarities
Indicates the sum of the absolute differences (L_1 norm) distance method.
L2_NORM - Static variable in class com.imsl.stat.Dissimilarities
Indicates the Euclidean distance method (L_2 norm).
label(int) - Static method in class com.imsl.Dummy
 
LABEL_TYPE_NONE - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate the an element is not to be labeled.
LABEL_TYPE_PERCENT - Static variable in class com.imsl.chart.ChartNode
Flag used to indicate that a pie slice is to be labeled with a percentage value.
LABEL_TYPE_TITLE - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that an element is to be labeled with the value of its title attribute.
LABEL_TYPE_X - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that an element is to be labeled with the value of its x-coordinate.
LABEL_TYPE_Y - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that an element is to be labeled with the value of its y-coordinate.
LABEL_TYPE_Z - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that an element is to be labeled with the value of its y-coordinate.
LackOfFit - Class in com.imsl.stat
Performs lack-of-fit test for a univariate time series or transfer function given the appropriate correlation function.
LAST - Static variable in class com.imsl.chart.Draw
Flag for the last data marker.
last() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the last row in this ResultSet object.
Layer - Class in com.imsl.datamining.neural
The base class for Layers in a neural network.
Layer(FeedForwardNetwork) - Constructor for class com.imsl.datamining.neural.Layer
Constructs a Layer.
LEAST_SQUARES - Static variable in class com.imsl.stat.ARAutoUnivariate
Indicates that least-squares should be used for estimating the coefficients in the time series.
LEAST_SQUARES - Static variable in class com.imsl.stat.ARMA
Indicates autoregressive and moving average parameters are estimated by a least-squares procedure.
LEAST_SQUARES - Static variable in class com.imsl.stat.ARMAEstimateMissing
Estimate autoregressive coefficients using least squares.
LeastSquaresTrainer - Class in com.imsl.datamining.neural
Trains a FeedForwardNetwork using a Levenberg-Marquardt algorithm for minimizing a sum of squares error.
LeastSquaresTrainer() - Constructor for class com.imsl.datamining.neural.LeastSquaresTrainer
Creates a LeastSquaresTrainer.
LEAVE_OUT_LAST - Static variable in class com.imsl.stat.RegressorsForGLM
The dummies are the first n-1 indicator variables.
LEAVE_OUT_ONE - Static variable in class com.imsl.stat.DiscriminantAnalysis
Indicates leave-out-one classification method.
leftBoundaries(double, double[][]) - Method in interface com.imsl.math.FeynmanKac.Boundaries
Returns the coefficient values of the left boundary conditions.
Legend - Class in com.imsl.chart
The chart legend.
Legend(Chart) - Constructor for class com.imsl.chart.Legend
 
LENGTH - Static variable in class com.imsl.math.Physical
 
LEVEL_SHIFT - Static variable in class com.imsl.stat.ARMAOutlierIdentification
Indicates detection of a level shift outlier.
LEVEL_SHIFT - Static variable in class com.imsl.stat.AutoARIMA
Indicates detection of a level shift outlier.
LicenseManagerException - Exception in com.imsl
A LicenseManagerException exception is thrown if a license to use the product cannot be obtained.
LifeTables - Class in com.imsl.stat
Computes population (current) or cohort life tables based upon the observed population sizes at the middle (for population table) or the beginning (for cohort table) of some user specified age intervals.
LifeTables(int[], double[], double[]) - Constructor for class com.imsl.stat.LifeTables
Constructs a new LifeTables instance.
LillieforsTest() - Method in class com.imsl.stat.NormalityTest
Performs the Lilliefors test.
LINE - Static variable in class com.imsl.chart.Draw
 
LINEAR - Static variable in interface com.imsl.datamining.neural.Activation
The identity activation function, g(x) = x.
LINEAR - Static variable in class com.imsl.stat.DiscriminantAnalysis
Indicates a linear discrimination method.
LINEAR_AT_RESTART_AND_TERMINATION - Static variable in class com.imsl.math.GenMinRes
Indicates residual updating is to be done by linear combination upon restarting and at termination.
LINEAR_AT_RESTART_ONLY - Static variable in class com.imsl.math.GenMinRes
Indicates residual updating is to be done by linear combination upon restarting only.
LinearRegression - Class in com.imsl.stat
Fits a multiple linear regression model with or without an intercept.
LinearRegression(int, boolean) - Constructor for class com.imsl.stat.LinearRegression
Constructs a new linear regression object.
LinearRegression.CaseStatistics - Class in com.imsl.stat
Inner Class CaseStatistics allows for the computation of predicted values, confidence intervals, and diagnostics for detecting outliers and cases that greatly influence the fitted regression.
LinearRegression.CoefficientTTests - Class in com.imsl.stat
Contains statistics related to the regression coefficients.
lineColor - Variable in class com.imsl.chart.Draw
 
lineDashPattern - Variable in class com.imsl.chart.Draw
 
lineWidth - Variable in class com.imsl.chart.Draw
 
link(Node, Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Establishes a Link between two Nodes.
link(Node, Node, double) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Establishes a Link between two Nodes with a specified weight.
Link - Class in com.imsl.datamining.neural
A link in a neural network.
LINKAGE_AVG_BETWEEN_CLUSTERS - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates the average distance between (average distance between objects in the two clusters) method.
LINKAGE_AVG_WITHIN_CLUSTERS - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates the average distance within (average distance between objects within the merged cluster) method.
LINKAGE_COMPLETE - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates the complete linkage (maximum distance) method.
LINKAGE_SINGLE - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates the single linkage (minimum distance) method.
LINKAGE_WARDS - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates the Ward's method.
linkAll(Layer, Layer) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Link all of the Nodes in one Layer to all of the Nodes in another Layer.
linkAll() - Method in class com.imsl.datamining.neural.FeedForwardNetwork
For each Layer in the Network, link each Node in the Layer to each Node in the next Layer.
log(Complex) - Static method in class com.imsl.math.Complex
Returns the logarithm of a Complex z, with a branch cut along the negative real axis.
log(double) - Static method in class com.imsl.math.JMath
Returns the natural logarithm of a double.
log10(double) - Static method in class com.imsl.math.Sfun
Returns the common (base 10) logarithm of a double.
log1p(double) - Static method in class com.imsl.math.Hyperbolic
Returns log(1+x), the logarithm of (x plus 1).
logBeta(double, double) - Static method in class com.imsl.math.Sfun
Returns the logarithm of the beta function.
logGamma(double) - Static method in class com.imsl.math.Sfun
Returns the logarithm of the Gamma function of the absolute value of a double.
logGammaCorrection(double) - Static method in class com.imsl.math.Sfun
Returns the log gamma correction term for argument values greater than or equal to 10.0.
LOGISTIC - Static variable in interface com.imsl.datamining.neural.Activation
The logistic activation function, g(x)=frac{1}{1+e^{-x}}.
logistic(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the logistic cumulative probability distribution function.
logistic(double, double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the logistic cumulative probability distribution function.
logistic(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the logistic probability density function.
LOGISTIC_TABLE - Static variable in interface com.imsl.datamining.neural.Activation
The logistic activation function computed using a table.
logNormal(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the standard lognormal cumulative probability distribution function.
logNormal(double, double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the standard lognormal cumulative probability distribution function.
logNormal(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the standard lognormal probability density function.
LogNormalDistribution - Class in com.imsl.stat
Evaluates a lognormal probability density for a given set of data.
LogNormalDistribution() - Constructor for class com.imsl.stat.LogNormalDistribution
 
longValue() - Method in class com.imsl.math.Complex
Returns the value of the real part as a long.
longValue() - Method in class com.imsl.math.Physical
Returns the value of this dimensionless object.
LOWER_TRIANGULAR - Static variable in class com.imsl.math.PrintMatrix
This flag as the argument to setMatrixType, indicates that only the lower triangular elements of the matrix are to be printed.
LU - Class in com.imsl.math
LU factorization of a matrix of type double.
LU(double[][]) - Constructor for class com.imsl.math.LU
Creates the > factorization of a square matrix of type double.

M

MAHALANOBIS - Static variable in class com.imsl.stat.Dissimilarities
Indicates the Mahalanobis distance method.
main(String[]) - Static method in class com.imsl.chart.xml.ChartXML
Displays a chart created from an XML file.
main(String[]) - Static method in class com.imsl.Version
Print the version information about the envirnoment and this library.
MajorTick - Class in com.imsl.chart
The major tick marks.
MajorTick - Class in com.imsl.chart3d
Major ticks marks.
MALLOWS_CP_CRITERION - Static variable in class com.imsl.stat.SelectionRegression
Indicates Mallow's C_p criterion regression.
mapCubeToUser(double, double, double, double[]) - Method in class com.imsl.chart3d.AxisXYZ
Map the cube coordinates to user coordinates.
mapDeviceToUser(int, int, double[]) - Method in class com.imsl.chart.Axis
Maps the device coordinates to user coordinates.
mapDeviceToUser(int, int, double[]) - Method in class com.imsl.chart.AxisXY
Map the device coordinates to user coordinates.
mapDeviceToUser(int, int, double[]) - Method in class com.imsl.chart.Pie
Maps the device coordinates to user coordinates.
mapDeviceToUser(int, int, double[]) - Method in class com.imsl.chart.Polar
Map the device coordinates to polar coordinates.
mapUnitToUser(double) - Method in interface com.imsl.chart.Transform
Maps points in the interval [0,1] to user coordinates.
mapUnitToUser(double) - Method in class com.imsl.chart.TransformDate
Maps points in the interval [0,1] to user coordinates.
mapUserToCube(double, double, double, double[]) - Method in class com.imsl.chart3d.AxisXYZ
Map the user coordinates (userX,userY) to the cube coordinates cubeXYZ.
mapUserToDevice(double, double, int[]) - Method in class com.imsl.chart.Axis
Maps the user coordinates (userX,userY) to the device coordinates devXY.
mapUserToDevice(double, double, int[]) - Method in class com.imsl.chart.AxisXY
Map the user coordinates (userX,userY) to the device coordinates devXY.
mapUserToDevice(double, double, int[]) - Method in class com.imsl.chart.Pie
Maps the user coordinates (userX,userY) to the device coordinates devXY.
mapUserToDevice(double, double, int[]) - Method in class com.imsl.chart.Polar
Map the polar coordinates (userRadius,userAngle) to the device coordinates devXY.
mapUserToUnit(double) - Method in interface com.imsl.chart.Transform
Maps user coordinate to the interval [0,1].
mapUserToUnit(double) - Method in class com.imsl.chart.TransformDate
Maps user coordinate to the interval [0,1].
MARKER - Static variable in class com.imsl.chart.Draw
 
MARKER_SCALE - Static variable in class com.imsl.chart.Draw
Normal marker size in pixels is screen width times MARKER_SCALE.
MARKER_TYPE_ASTERISK - Static variable in class com.imsl.chart.ChartNode
Flag for a asterisk data marker.
MARKER_TYPE_CIRCLE_CIRCLE - Static variable in class com.imsl.chart.ChartNode
Flag for a circle in a circle data marker.
MARKER_TYPE_CIRCLE_PLUS - Static variable in class com.imsl.chart.ChartNode
Flag for a plus in a circle data marker.
MARKER_TYPE_CIRCLE_X - Static variable in class com.imsl.chart.ChartNode
Flag for an x in a circle data marker.
MARKER_TYPE_CUBE - Static variable in class com.imsl.chart3d.ChartNode3D
Flag for a cube data marker.
MARKER_TYPE_CUSTOM - Static variable in class com.imsl.chart3d.ChartNode3D
Flag for a custom marker
MARKER_TYPE_DIAMOND_PLUS - Static variable in class com.imsl.chart.ChartNode
Flag for a plus in a diamond data marker.
MARKER_TYPE_FILLED_CIRCLE - Static variable in class com.imsl.chart.ChartNode
Flag for a filled circle data marker.
MARKER_TYPE_FILLED_DIAMOND - Static variable in class com.imsl.chart.ChartNode
Flag for a filled diamond data marker.
MARKER_TYPE_FILLED_SQUARE - Static variable in class com.imsl.chart.ChartNode
Flag for a filled square data marker.
MARKER_TYPE_FILLED_TRIANGLE - Static variable in class com.imsl.chart.ChartNode
Flag for a filled triangle data marker.
MARKER_TYPE_HOLLOW_CIRCLE - Static variable in class com.imsl.chart.ChartNode
Flag for a hollow circle data marker.
MARKER_TYPE_HOLLOW_DIAMOND - Static variable in class com.imsl.chart.ChartNode
Flag for a hollow diamond data marker.
MARKER_TYPE_HOLLOW_SQUARE - Static variable in class com.imsl.chart.ChartNode
Flag for a hollow square data marker.
MARKER_TYPE_HOLLOW_TRIANGLE - Static variable in class com.imsl.chart.ChartNode
Flag for hollow triangle data marker.
MARKER_TYPE_OCTAGON_PLUS - Static variable in class com.imsl.chart.ChartNode
Flag for a plus in an octagon data marker.
MARKER_TYPE_OCTAGON_X - Static variable in class com.imsl.chart.ChartNode
Flag for a x in an octagon data marker.
MARKER_TYPE_PLUS - Static variable in class com.imsl.chart.ChartNode
Flag for a plus-shaped data marker.
MARKER_TYPE_PLUS - Static variable in class com.imsl.chart3d.ChartNode3D
Flag for a 3D plus sign data marker.
MARKER_TYPE_SIMPLE_CUBE - Static variable in class com.imsl.chart3d.ChartNode3D
Flag for a simple cube (no edge) data marker.
MARKER_TYPE_SIMPLE_PLUS - Static variable in class com.imsl.chart3d.ChartNode3D
Flag for a simple 2D plus sign (no edge) data marker.
MARKER_TYPE_SIMPLE_TETRAHEDRON - Static variable in class com.imsl.chart3d.ChartNode3D
Flag for a simple tetrahedron (no edge) data marker.
MARKER_TYPE_SPHERE - Static variable in class com.imsl.chart3d.ChartNode3D
Flag for a sphere data marker.
MARKER_TYPE_SQUARE_PLUS - Static variable in class com.imsl.chart.ChartNode
Flag for a plus in a square data marker.
MARKER_TYPE_SQUARE_X - Static variable in class com.imsl.chart.ChartNode
Flag for an x in a square data marker.
MARKER_TYPE_TETRAHEDRON - Static variable in class com.imsl.chart3d.ChartNode3D
Flag for a tetrahedron data marker.
MARKER_TYPE_X - Static variable in class com.imsl.chart.ChartNode
Flag for a x-shaped data marker.
markerColor - Variable in class com.imsl.chart.Draw
 
markerDashPattern - Variable in class com.imsl.chart.Draw
 
markerSize - Variable in class com.imsl.chart.Draw
 
markerThickness - Variable in class com.imsl.chart.Draw
 
markerType - Variable in class com.imsl.chart.Draw
 
MASS - Static variable in class com.imsl.math.Physical
 
Matrix - Class in com.imsl.math
Matrix manipulation functions.
max(int, int) - Static method in class com.imsl.math.JMath
Returns the larger of two ints.
max(long, long) - Static method in class com.imsl.math.JMath
Returns the larger of two longs.
max(float, float) - Static method in class com.imsl.math.JMath
Returns the larger of two floats.
max(double, double) - Static method in class com.imsl.math.JMath
Returns the larger of two doubles.
MAX_LIKELIHOOD - Static variable in class com.imsl.stat.ARAutoUnivariate
Indicates that maximum likelihood should be used for estimating the coefficients in the time series.
MAX_LIKELIHOOD - Static variable in class com.imsl.stat.ARMAEstimateMissing
Estimate autoregressive coefficients using maximum likelihood.
maximum(double[]) - Static method in class com.imsl.stat.Summary
Returns the maximum of the given data set.
maximum(int[]) - Static method in class com.imsl.stat.Summary
Returns the maximum of the given data set.
MAXIMUM_LIKELIHOOD - Static variable in class com.imsl.stat.FactorAnalysis
Indicates maximum likelihood method.
MAXIMUM_SUPERNODE_SIZE - Static variable in class com.imsl.math.ComplexSuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
MAXIMUM_SUPERNODE_SIZE - Static variable in class com.imsl.math.SuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
mduration(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the modified Macauley duration for a security with an assumed par value of $100.
mean(double[]) - Static method in class com.imsl.stat.Summary
Returns the mean of the given data set.
mean(double[], double[]) - Static method in class com.imsl.stat.Summary
Returns the mean of the given data set with associated weights.
MEDIAN - Static variable in class com.imsl.stat.ARMAEstimateMissing
Indicates that missing values should be estimated using the median of the values just before and after the missing value gap.
median(double[]) - Static method in class com.imsl.stat.Summary
Returns the median of the given data set.
MersenneTwister - Class in com.imsl.stat
A 32-bit Mersenne Twister generator.
MersenneTwister(int) - Constructor for class com.imsl.stat.MersenneTwister
Constructor for the MersenneTwister class with supplied seed.
MersenneTwister(int[]) - Constructor for class com.imsl.stat.MersenneTwister
Constructor for the MersenneTwister class with supplied array.
MersenneTwister64 - Class in com.imsl.stat
A 64-bit Mersenne Twister generator.
MersenneTwister64(long) - Constructor for class com.imsl.stat.MersenneTwister64
Constructor for the MersenneTwister64 class with supplied seed.
MersenneTwister64(long[]) - Constructor for class com.imsl.stat.MersenneTwister64
Constructor for the MersenneTwister64 class with supplied array.
Messages - Class in com.imsl
Retrieve and format message strings.
Messages() - Constructor for class com.imsl.Messages
 
METHOD_ADAMS - Static variable in class com.imsl.math.OdeAdamsGear
The Adams integration method
METHOD_BDF - Static variable in class com.imsl.math.OdeAdamsGear
The BDF integration method
METHOD_OF_MOMENTS - Static variable in class com.imsl.stat.ARAutoUnivariate
Indicates the method of moments should be used for estimating the coefficients in the time series.
METHOD_OF_MOMENTS - Static variable in class com.imsl.stat.ARMA
Indicates autoregressive and moving average parameters are estimated by a method of moments procedure.
METHOD_OF_MOMENTS - Static variable in class com.imsl.stat.ARMAEstimateMissing
Estimate autoregressive coefficients using method of moments.
METHOD_OF_PETZOLD - Static variable in class com.imsl.math.FeynmanKac
Used by method setStepControlMethod to indicate that the step control algorithm of the original Petzold code is used in the integration.
METHOD_OF_SOEDERLIND - Static variable in class com.imsl.math.FeynmanKac
Used by method setStepControlMethod to indicate that the step control method by Soederlind is used in the integration.
min(int, int) - Static method in class com.imsl.math.JMath
Returns the smaller of two ints.
min(long, long) - Static method in class com.imsl.math.JMath
Returns the smaller of two longs.
min(float, float) - Static method in class com.imsl.math.JMath
Returns the smaller of two floats.
min(double, double) - Static method in class com.imsl.math.JMath
Returns the smaller of two doubles.
MinConGenLin - Class in com.imsl.math
Minimizes a general objective function subject to linear equality/inequality constraints.
MinConGenLin(MinConGenLin.Function, int, int, int, double[], double[], double[], double[]) - Constructor for class com.imsl.math.MinConGenLin
Constructor for MinConGenLin.
MinConGenLin.ConstraintsInconsistentException - Exception in com.imsl.math
The equality constraints are inconsistent.
MinConGenLin.ConstraintsInconsistentException(String) - Constructor for exception com.imsl.math.MinConGenLin.ConstraintsInconsistentException
 
MinConGenLin.ConstraintsInconsistentException(String, Object[]) - Constructor for exception com.imsl.math.MinConGenLin.ConstraintsInconsistentException
 
MinConGenLin.ConstraintsNotSatisfiedException - Exception in com.imsl.math
No vector x satisfies all of the constraints.
MinConGenLin.ConstraintsNotSatisfiedException(String) - Constructor for exception com.imsl.math.MinConGenLin.ConstraintsNotSatisfiedException
 
MinConGenLin.ConstraintsNotSatisfiedException(String, Object[]) - Constructor for exception com.imsl.math.MinConGenLin.ConstraintsNotSatisfiedException
 
MinConGenLin.EqualityConstraintsException - Exception in com.imsl.math
the variables are determined by the equality constraints.
MinConGenLin.EqualityConstraintsException(String) - Constructor for exception com.imsl.math.MinConGenLin.EqualityConstraintsException
 
MinConGenLin.EqualityConstraintsException(String, Object[]) - Constructor for exception com.imsl.math.MinConGenLin.EqualityConstraintsException
 
MinConGenLin.Function - Interface in com.imsl.math
Public interface for the user-supplied function to evaluate the function to be minimized.
MinConGenLin.Gradient - Interface in com.imsl.math
Public interface for the user-supplied function to compute the gradient.
MinConGenLin.VarBoundsInconsistentException - Exception in com.imsl.math
The equality constraints and the bounds on the variables are found to be inconsistent.
MinConGenLin.VarBoundsInconsistentException(String) - Constructor for exception com.imsl.math.MinConGenLin.VarBoundsInconsistentException
 
MinConGenLin.VarBoundsInconsistentException(String, Object[]) - Constructor for exception com.imsl.math.MinConGenLin.VarBoundsInconsistentException
 
MinConNLP - Class in com.imsl.math
General nonlinear programming solver.
MinConNLP(int, int, int) - Constructor for class com.imsl.math.MinConNLP
Nonlinear programming solver constructor.
MinConNLP.BadInitialGuessException - Exception in com.imsl.math
Penalty function point infeasible for original problem.
MinConNLP.BadInitialGuessException(String) - Constructor for exception com.imsl.math.MinConNLP.BadInitialGuessException
 
MinConNLP.BadInitialGuessException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.BadInitialGuessException
 
MinConNLP.ConstraintEvaluationException - Exception in com.imsl.math
Constraint evaluation returns an error with current point.
MinConNLP.ConstraintEvaluationException(String) - Constructor for exception com.imsl.math.MinConNLP.ConstraintEvaluationException
 
MinConNLP.ConstraintEvaluationException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.ConstraintEvaluationException
 
MinConNLP.Function - Interface in com.imsl.math
Public interface for the user supplied function to the MinConNLP object.
MinConNLP.Gradient - Interface in com.imsl.math
Public interface for the user supplied function to compute the gradient for MinConNLP object.
MinConNLP.IllConditionedException - Exception in com.imsl.math
Problem is singular or ill-conditioned.
MinConNLP.IllConditionedException(String) - Constructor for exception com.imsl.math.MinConNLP.IllConditionedException
 
MinConNLP.IllConditionedException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.IllConditionedException
 
MinConNLP.LimitingAccuracyException - Exception in com.imsl.math
Limiting accuracy reached for a singular problem.
MinConNLP.LimitingAccuracyException(String) - Constructor for exception com.imsl.math.MinConNLP.LimitingAccuracyException
 
MinConNLP.LimitingAccuracyException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.LimitingAccuracyException
 
MinConNLP.LinearlyDependentGradientsException - Exception in com.imsl.math
Working set gradients are linearly dependent.
MinConNLP.LinearlyDependentGradientsException(String) - Constructor for exception com.imsl.math.MinConNLP.LinearlyDependentGradientsException
 
MinConNLP.LinearlyDependentGradientsException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.LinearlyDependentGradientsException
 
MinConNLP.NoAcceptableStepsizeException - Exception in com.imsl.math
No acceptable stepsize in [SIGMA,SIGLA].
MinConNLP.NoAcceptableStepsizeException(String) - Constructor for exception com.imsl.math.MinConNLP.NoAcceptableStepsizeException
 
MinConNLP.NoAcceptableStepsizeException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.NoAcceptableStepsizeException
 
MinConNLP.ObjectiveEvaluationException - Exception in com.imsl.math
Objective evaluation returns an error with current point.
MinConNLP.ObjectiveEvaluationException(String) - Constructor for exception com.imsl.math.MinConNLP.ObjectiveEvaluationException
 
MinConNLP.ObjectiveEvaluationException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.ObjectiveEvaluationException
 
MinConNLP.PenaltyFunctionPointInfeasibleException - Exception in com.imsl.math
Penalty function point infeasible.
MinConNLP.PenaltyFunctionPointInfeasibleException(String) - Constructor for exception com.imsl.math.MinConNLP.PenaltyFunctionPointInfeasibleException
 
MinConNLP.PenaltyFunctionPointInfeasibleException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.PenaltyFunctionPointInfeasibleException
 
MinConNLP.QPInfeasibleException - Exception in com.imsl.math
QP problem seemingly infeasible.
MinConNLP.QPInfeasibleException(String) - Constructor for exception com.imsl.math.MinConNLP.QPInfeasibleException
 
MinConNLP.QPInfeasibleException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.QPInfeasibleException
 
MinConNLP.SingularException - Exception in com.imsl.math
Problem is singular.
MinConNLP.SingularException(String) - Constructor for exception com.imsl.math.MinConNLP.SingularException
 
MinConNLP.SingularException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.SingularException
 
MinConNLP.TerminationCriteriaNotSatisfiedException - Exception in com.imsl.math
Termination criteria are not satisfied.
MinConNLP.TerminationCriteriaNotSatisfiedException(String) - Constructor for exception com.imsl.math.MinConNLP.TerminationCriteriaNotSatisfiedException
 
MinConNLP.TerminationCriteriaNotSatisfiedException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.TerminationCriteriaNotSatisfiedException
 
MinConNLP.TooManyIterationsException - Exception in com.imsl.math
Maximum number of iterations exceeded.
MinConNLP.TooManyIterationsException(String) - Constructor for exception com.imsl.math.MinConNLP.TooManyIterationsException
 
MinConNLP.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.TooManyIterationsException
 
MinConNLP.TooMuchTimeException - Exception in com.imsl.math
Maximum time allowed for solve exceeded.
MinConNLP.TooMuchTimeException(long) - Constructor for exception com.imsl.math.MinConNLP.TooMuchTimeException
 
MinConNLP.WorkingSetSingularException - Exception in com.imsl.math
Working set is singular in dual extended QP.
MinConNLP.WorkingSetSingularException(String) - Constructor for exception com.imsl.math.MinConNLP.WorkingSetSingularException
 
MinConNLP.WorkingSetSingularException(String, Object[]) - Constructor for exception com.imsl.math.MinConNLP.WorkingSetSingularException
 
minimum(double[]) - Static method in class com.imsl.stat.Summary
Returns the minimum of the given data set.
minimum(int[]) - Static method in class com.imsl.stat.Summary
Returns the minimum of the given data set.
MINIMUM_COLUMN_DIMENSION - Static variable in class com.imsl.math.ComplexSuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
MINIMUM_COLUMN_DIMENSION - Static variable in class com.imsl.math.SuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
MINIMUM_DEGREE_AT_A - Static variable in class com.imsl.math.ComplexSuperLU
For column ordering, use minimum degree ordering on the structure of A^TA.
MINIMUM_DEGREE_AT_A - Static variable in class com.imsl.math.SuperLU
For column ordering, use minimum degree ordering on the structure of A^TA.
MINIMUM_DEGREE_AT_PLUS_A - Static variable in class com.imsl.math.ComplexSuperLU
For column ordering, use minimum degree ordering on the structure of A^T+A.
MINIMUM_DEGREE_AT_PLUS_A - Static variable in class com.imsl.math.SuperLU
For column ordering, use minimum degree ordering on the structure of A^T+A.
MINIMUM_ROW_DIMENSION - Static variable in class com.imsl.math.ComplexSuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
MINIMUM_ROW_DIMENSION - Static variable in class com.imsl.math.SuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
MinorTick - Class in com.imsl.chart
The minor tick marks.
MinUncon - Class in com.imsl.math
Unconstrained minimization.
MinUncon() - Constructor for class com.imsl.math.MinUncon
Unconstrained minimum constructor for a smooth function of a single variable of type double.
MinUncon.Derivative - Interface in com.imsl.math
Public interface for the user supplied function to the MinUncon object.
MinUncon.Function - Interface in com.imsl.math
Public interface for the user supplied function to the MinUncon object.
MinUnconMultiVar - Class in com.imsl.math
Unconstrained multivariate minimization.
MinUnconMultiVar(int) - Constructor for class com.imsl.math.MinUnconMultiVar
Unconstrained minimum constructor for a function of n variables of type double.
MinUnconMultiVar.ApproximateMinimumException - Exception in com.imsl.math
Scaled step tolerance satisfied; the current point may be an approximate local solution, or the algorithm is making very slow progress and is not near a solution, or the scaled step tolerance is too big.
MinUnconMultiVar.ApproximateMinimumException(String) - Constructor for exception com.imsl.math.MinUnconMultiVar.ApproximateMinimumException
 
MinUnconMultiVar.ApproximateMinimumException(String, Object[]) - Constructor for exception com.imsl.math.MinUnconMultiVar.ApproximateMinimumException
 
MinUnconMultiVar.FalseConvergenceException - Exception in com.imsl.math
False convergence error; the iterates appear to be converging to a noncritical point.
MinUnconMultiVar.FalseConvergenceException(String) - Constructor for exception com.imsl.math.MinUnconMultiVar.FalseConvergenceException
 
MinUnconMultiVar.FalseConvergenceException(String, Object[]) - Constructor for exception com.imsl.math.MinUnconMultiVar.FalseConvergenceException
 
MinUnconMultiVar.Function - Interface in com.imsl.math
Public interface for the user supplied function to the MinUnconMultiVar object.
MinUnconMultiVar.Gradient - Interface in com.imsl.math
Public interface for the user supplied gradient to the MinUnconMultiVar object.
MinUnconMultiVar.Hessian - Interface in com.imsl.math
Public interface for the user supplied Hessian to the MinUnconMultiVar object.
MinUnconMultiVar.MaxIterationsException - Exception in com.imsl.math
Maximum number of iterations exceeded.
MinUnconMultiVar.MaxIterationsException(String) - Constructor for exception com.imsl.math.MinUnconMultiVar.MaxIterationsException
 
MinUnconMultiVar.MaxIterationsException(String, Object[]) - Constructor for exception com.imsl.math.MinUnconMultiVar.MaxIterationsException
 
MinUnconMultiVar.UnboundedBelowException - Exception in com.imsl.math
Five consecutive steps of the maximum allowable stepsize have been taken, either the function is unbounded below, or has a finite asymptote in some direction or the maximum allowable step size is too small.
MinUnconMultiVar.UnboundedBelowException(String) - Constructor for exception com.imsl.math.MinUnconMultiVar.UnboundedBelowException
 
MinUnconMultiVar.UnboundedBelowException(String, Object[]) - Constructor for exception com.imsl.math.MinUnconMultiVar.UnboundedBelowException
 
mirr(double[], double, double) - Static method in class com.imsl.finance.Finance
Returns the modified internal rate of return for a schedule of periodic cash flows.
mode(double[]) - Static method in class com.imsl.stat.Summary
Returns the mode of the given data set.
MODEL0 - Static variable in class com.imsl.stat.CategoricalGenLinModel
Indicates an exponential function is used to model the distribution parameter.
MODEL1 - Static variable in class com.imsl.stat.CategoricalGenLinModel
Indicates a logistic function is used to model the distribution parameter.
MODEL2 - Static variable in class com.imsl.stat.CategoricalGenLinModel
Indicates a logistic function is used to model the distribution parameter.
MODEL3 - Static variable in class com.imsl.stat.CategoricalGenLinModel
Indicates a logistic function is used to model the distribution parameter.
MODEL4 - Static variable in class com.imsl.stat.CategoricalGenLinModel
Indicates a probit function is used to model the distribution parameter.
MODEL5 - Static variable in class com.imsl.stat.CategoricalGenLinModel
Indicates a log-log function is used to model the distribution parameter.
MONTHLY - Static variable in class com.imsl.finance.Bond
Coupon payments are made monthly.
MORANS_FORMULA - Static variable in class com.imsl.stat.AutoCorrelation
Indicates standard error computation using Moran's formula.
mouseDragged(MouseEvent) - Method in class com.imsl.chart.ToolTip
Part of the MouseMotionListener interface.
mouseMoved(MouseEvent) - Method in class com.imsl.chart.ToolTip
Part of the MouseMotionListener interface.
moveToCurrentRow() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the remembered cursor position, usually the current row.
moveToInsertRow() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the insert row.
MPSReader - Class in com.imsl.io
Reads a linear programming problem from an MPS file.
MPSReader() - Constructor for class com.imsl.io.MPSReader
 
MPSReader.Element - Class in com.imsl.io
An element in the sparse contraint matrix.
MPSReader.InvalidMPSFileException - Exception in com.imsl.io
The MPS file is invalid.
MPSReader.InvalidMPSFileException(String) - Constructor for exception com.imsl.io.MPSReader.InvalidMPSFileException
 
MPSReader.InvalidMPSFileException(String, Object[]) - Constructor for exception com.imsl.io.MPSReader.InvalidMPSFileException
 
MPSReader.Row - Class in com.imsl.io
A row either in the constraint matrix or a free row.
mu(double, double) - Method in interface com.imsl.math.FeynmanKac.PdeCoefficients
Returns the value of the mu coefficient at the given point.
MultiClassification - Class in com.imsl.datamining.neural
Classifies patterns into three or more classes.
MultiClassification(Network) - Constructor for class com.imsl.datamining.neural.MultiClassification
Creates a classifier.
MultiCrossCorrelation - Class in com.imsl.stat
Computes the multichannel cross-correlation function of two mutually stationary multichannel time series.
MultiCrossCorrelation(double[][], double[][], int) - Constructor for class com.imsl.stat.MultiCrossCorrelation
Constructor to compute the multichannel cross-correlation function of two mutually stationary multichannel time series.
MultiCrossCorrelation.NonPosVariancesException - Exception in com.imsl.stat
The problem is ill-conditioned.
MultiCrossCorrelation.NonPosVariancesException(String) - Constructor for exception com.imsl.stat.MultiCrossCorrelation.NonPosVariancesException
 
MultiCrossCorrelation.NonPosVariancesException(String, Object[]) - Constructor for exception com.imsl.stat.MultiCrossCorrelation.NonPosVariancesException
 
MULTIFRONTAL_METHOD - Static variable in class com.imsl.math.ComplexSparseCholesky
Indicates the multifrontal method will be used for numeric factorization.
MULTIFRONTAL_METHOD - Static variable in class com.imsl.math.SparseCholesky
Indicates the multifrontal method will be used for numeric factorization.
MultipleComparisons - Class in com.imsl.stat
Performs Student-Newman-Keuls multiple comparisons test.
MultipleComparisons(double[], int, double) - Constructor for class com.imsl.stat.MultipleComparisons
Constructor for MultipleComparisons.
MULTIPLICATION - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates transformation by multiplication by -1.0.
multiply(Complex, Complex) - Static method in class com.imsl.math.Complex
Returns the product of two Complex objects, x * y.
multiply(Complex, double) - Static method in class com.imsl.math.Complex
Returns the product of a Complex object and a double, x * y.
multiply(double, Complex) - Static method in class com.imsl.math.Complex
Returns the product of a double and a Complex object, x * y.
multiply(Complex[], Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Return the product of the row vector x and the rectangular array a, both Complex.
multiply(Complex[][], Complex[]) - Static method in class com.imsl.math.ComplexMatrix
Multiply the rectangular array a and the column vector x, both Complex.
multiply(Complex[][], Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Multiply two Complex rectangular arrays, a * b.
multiply(Complex[][], Complex[][], int) - Static method in class com.imsl.math.ComplexMatrix
Multiply two Complex rectangular arrays, a * b, using multiple processors.
multiply(Complex[]) - Method in class com.imsl.math.ComplexSparseMatrix
Multiply the matrix by a vector.
multiply(ComplexSparseMatrix, Complex[]) - Static method in class com.imsl.math.ComplexSparseMatrix
Multiply sparse matrix A and column array x, A x.
multiply(Complex[], ComplexSparseMatrix) - Static method in class com.imsl.math.ComplexSparseMatrix
Multiply row array x and sparse matrix A, x^TA.
multiply(ComplexSparseMatrix, ComplexSparseMatrix) - Static method in class com.imsl.math.ComplexSparseMatrix
Multiply two sparse complex matrices A and B, C leftarrow AB.
multiply(double[], double[][]) - Static method in class com.imsl.math.Matrix
Return the product of the row array x and the rectangular array a.
multiply(double[][], double[]) - Static method in class com.imsl.math.Matrix
Multiply the rectangular array a and the column array x.
multiply(double[][], double[][]) - Static method in class com.imsl.math.Matrix
Multiply two rectangular arrays, a * b.
multiply(double[][], double[][], int) - Static method in class com.imsl.math.Matrix
Multiply two rectangular arrays, a * b, using multiple processors.
multiply(Physical, Physical) - Static method in class com.imsl.math.Physical
Multiply two Physical objects.
multiply(Physical, double) - Static method in class com.imsl.math.Physical
Multiply a Physical object and a double
multiply(double, Physical) - Static method in class com.imsl.math.Physical
Multiply a double and a Physical object
multiply(double[]) - Method in class com.imsl.math.SparseMatrix
Multiply the matrix by a vector.
multiply(SparseMatrix, double[]) - Static method in class com.imsl.math.SparseMatrix
Multiply sparse matrix A and column array x, A x.
multiply(double[], SparseMatrix) - Static method in class com.imsl.math.SparseMatrix
Multiply row array x and sparse matrix A, x^TA.
multiply(SparseMatrix, SparseMatrix) - Static method in class com.imsl.math.SparseMatrix
Multiply two sparse matrices A and B, C leftarrow AB.
multiplyHermitian(ComplexSparseMatrix, Complex[]) - Static method in class com.imsl.math.ComplexSparseMatrix
Multiply sparse Hermitian matrix A and column vector x.
multiplyImag(Complex, double) - Static method in class com.imsl.math.Complex
Returns the product of a Complex object and a pure imaginary double, x * iy.
multiplyImag(double, Complex) - Static method in class com.imsl.math.Complex
Returns the product of a pure imaginary double and a Complex object, ix * y.
multiplySymmetric(SparseMatrix, double[]) - Static method in class com.imsl.math.SparseMatrix
Multiply sparse symmetric matrix A and column vector x.

N

NaiveBayesClassifier - Class in com.imsl.datamining
Trains a Naive Bayes Classifier
NaiveBayesClassifier(int, int, int) - Constructor for class com.imsl.datamining.NaiveBayesClassifier
Constructs a NaiveBayesClassifier
NATURAL_ORDERING - Static variable in class com.imsl.math.ComplexSuperLU
For column ordering, use the natural ordering.
NATURAL_ORDERING - Static variable in class com.imsl.math.SuperLU
For column ordering, use the natural ordering.
nCoef - Variable in class com.imsl.math.BsLeastSquares
Number of B-spline coefficients.
negate(Complex) - Static method in class com.imsl.math.Complex
Returns the negative of a Complex object, -z.
negate(Physical) - Static method in class com.imsl.math.Physical
Negate a Physical object.
Network - Class in com.imsl.datamining.neural
Neural network base class.
Network() - Constructor for class com.imsl.datamining.neural.Network
Default constructor for Network.
next() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor down one row from its current position.
next(int) - Method in class com.imsl.stat.MersenneTwister
Generates the next pseudorandom number.
next(int) - Method in class com.imsl.stat.MersenneTwister64
Generates the next pseudorandom number.
next(int) - Method in interface com.imsl.stat.Random.BaseGenerator
Generates the next pseudorandom number.
next(int) - Method in class com.imsl.stat.Random
Generates the next pseudorandom number.
nextAfter(double, double) - Static method in class com.imsl.math.IEEE
Returns the next machine floating-point number next to x in the direction toward y.
nextBeta(double, double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a beta distribution.
nextBinomial(int, double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a binomial distribution.
nextCauchy() - Method in class com.imsl.stat.Random
Generates a pseudorandom number from a Cauchy distribution.
nextChiSquared(double) - Method in class com.imsl.stat.Random
Generates a pseudorandom number from a Chi-squared distribution.
nextDouble() - Method in class com.imsl.stat.FaureSequence
Returns the first value of the next point in the sequence.
nextDouble() - Method in class com.imsl.stat.MersenneTwister
Generates the next pseudorandom, uniformly distributed double value from this random number generator's sequence.
nextDouble() - Method in class com.imsl.stat.MersenneTwister64
Generates the next pseudorandom, uniformly distributed double value from this random number generator's sequence.
nextExponential() - Method in class com.imsl.stat.Random
Generates a pseudorandom number from a standard exponential distribution.
nextExponentialMix(double, double, double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a mixture of two exponential distributions.
nextExtremeValue(double, double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from an extreme value distribution.
nextF(double, double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from the F distribution.
nextFloat() - Method in class com.imsl.stat.MersenneTwister
Generates the next pseudorandom, uniformly distributed float value from this random number generator's sequence.
nextFloat() - Method in class com.imsl.stat.MersenneTwister64
Generates the next pseudorandom, uniformly distributed float value from this random number generator's sequence.
nextGamma(double) - Method in class com.imsl.stat.Random
Generates a pseudorandom number from a standard gamma distribution.
nextGaussianCopula(Cholesky) - Method in class com.imsl.stat.Random
Generate pseudorandom numbers from a Gaussian Copula distribution.
nextGeometric(double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a geometric distribution.
nextHypergeometric(int, int, int) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a hypergeometric distribution.
nextInt() - Method in class com.imsl.stat.MersenneTwister
Generates the next pseudorandom number.
nextLogarithmic(double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a logarithmic distribution.
nextLogNormal(double, double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a lognormal distribution.
nextLong() - Method in class com.imsl.stat.MersenneTwister64
Generates the next pseudorandom, uniformly distributed long value from this random number generator's sequence.
nextMultivariateNormal(Cholesky) - Method in class com.imsl.stat.Random
Generate pseudorandom numbers from a multivariate normal distribution.
nextNegativeBinomial(double, double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a negative binomial distribution.
nextNormal() - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a standard normal distribution using an inverse CDF method.
nextPoint() - Method in class com.imsl.stat.FaureSequence
Returns the next point in the sequence.
nextPoint() - Method in interface com.imsl.stat.RandomSequence
Returns the next multidimensional point in the sequence.
nextPoisson(double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a Poisson distribution.
nextPrime(int) - Static method in class com.imsl.stat.FaureSequence
Returns the smallest prime greater than or equal to n.
nextRayleigh(double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a Rayleigh distribution.
nextStudentsT(double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a Student's t distribution.
nextStudentsTCopula(double, Cholesky) - Method in class com.imsl.stat.Random
Generate pseudorandom numbers from a Student's t Copula distribution.
nextToken() - Method in class com.imsl.io.Tokenizer
Returns the next token.
nextTriangular() - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a triangular distribution on the interval (0,1).
nextVonMises(double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a von Mises distribution.
nextWeibull(double) - Method in class com.imsl.stat.Random
Generate a pseudorandom number from a Weibull distribution.
nextZigguratNormalAR() - Method in class com.imsl.stat.Random
Generates pseudorandom numbers using the Ziggurat method.
nFunctionEvaluations - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.GradObjective
 
nFunctionEvaluations - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective
 
NO_CENTER - Static variable in class com.imsl.stat.ARSeasonalFit
Indicates the transformed series should not be centered.
NO_SCALING - Static variable in class com.imsl.datamining.neural.ScaleFilter
Flag to indicate no scaling.
NO_SCALING - Static variable in class com.imsl.math.ComplexSuperLU
Indicates that input matrix A was not equilibrated before factorization.
NO_SCALING - Static variable in class com.imsl.math.SuperLU
Indicates that input matrix A was not equilibrated before factorization.
NO_SCALING - Static variable in class com.imsl.stat.Dissimilarities
Indicates no scaling.
nObs - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.GradObjective
 
nObs - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective
 
node - Variable in class com.imsl.chart.Draw
 
Node - Class in com.imsl.datamining.neural
A Node in a neural network.
nominal(double, int) - Static method in class com.imsl.finance.Finance
Returns the nominal annual interest rate.
noncentralBeta(double, double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the noncentral beta cumulative distribution function (CDF).
noncentralBeta(double, double, double, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the noncentral beta cumulative distribution function (CDF).
noncentralBeta(double, double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the noncentral beta probability density function (PDF).
noncentralchi(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the noncentral chi-squared cumulative probability distribution function.
noncentralchi(double, double, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the noncentral chi-squared cumulative probability distribution function.
noncentralChi(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the noncentral chi-squared probability density function (PDF).
noncentralF(double, double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the noncentral F cumulative distribution function.
noncentralF(double, double, double, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the noncentral F cumulative distribution function (CDF).
noncentralF(double, double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the noncentral F probability density function (PDF).
noncentralstudentsT(double, int, double) - Static method in class com.imsl.stat.Cdf
Evaluates the noncentral Student's t cumulative probability distribution function.
noncentralstudentsT(double, int, double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the noncentral Student's t cumulative probability distribution function.
noncentralStudentsT(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the noncentral Student's t probability density function.
NONE - Static variable in class com.imsl.chart.Draw
 
NONE - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates no transformation.
NonlinearRegression - Class in com.imsl.stat
Fits a multivariate nonlinear regression model using least squares.
NonlinearRegression(int) - Constructor for class com.imsl.stat.NonlinearRegression
Constructs a new nonlinear regression object.
NonlinearRegression.Derivative - Interface in com.imsl.stat
Public interface for the user supplied function to compute the derivative for NonlinearRegression.
NonlinearRegression.Function - Interface in com.imsl.stat
Public interface for the user supplied function for NonlinearRegression.
NonlinearRegression.NegativeFreqException - Exception in com.imsl.stat
A negative frequency was encountered.
NonlinearRegression.NegativeFreqException(int, int, double) - Constructor for exception com.imsl.stat.NonlinearRegression.NegativeFreqException
Constructs a NegativeFreqException.
NonlinearRegression.NegativeWeightException - Exception in com.imsl.stat
A negative weight was encountered.
NonlinearRegression.NegativeWeightException(int, int, double) - Constructor for exception com.imsl.stat.NonlinearRegression.NegativeWeightException
Constructs a NegativeWeightException.
NonlinearRegression.NoProgressException - Exception in com.imsl.stat
The algorithm is not making any progress, try new initial guess.
NonlinearRegression.NoProgressException() - Constructor for exception com.imsl.stat.NonlinearRegression.NoProgressException
 
NonlinearRegression.NoProgressException(String, Object[]) - Constructor for exception com.imsl.stat.NonlinearRegression.NoProgressException
 
NonlinearRegression.NoProgressException(Object[]) - Constructor for exception com.imsl.stat.NonlinearRegression.NoProgressException
 
NonlinearRegression.TooManyIterationsException - Exception in com.imsl.stat
The number of iterations has exceeded the maximum allowed.
NonlinearRegression.TooManyIterationsException() - Constructor for exception com.imsl.stat.NonlinearRegression.TooManyIterationsException
Constructs a TooManyIterationsException.
NonlinLeastSquares - Class in com.imsl.math
Nonlinear least squares.
NonlinLeastSquares(int, int) - Constructor for class com.imsl.math.NonlinLeastSquares
Creates an object to solve a nonlinear least squares problem.
NonlinLeastSquares.Function - Interface in com.imsl.math
Public interface for the user supplied function to the NonlinLeastSquares object.
NonlinLeastSquares.Jacobian - Interface in com.imsl.math
Public interface for the user supplied function to the NonlinLeastSquares object.
NonlinLeastSquares.NoProgressException - Exception in com.imsl.math
The algorithm is not making any progress, try new initial guess.
NonlinLeastSquares.NoProgressException() - Constructor for exception com.imsl.math.NonlinLeastSquares.NoProgressException
 
NonlinLeastSquares.NoProgressException(String, Object[]) - Constructor for exception com.imsl.math.NonlinLeastSquares.NoProgressException
 
NonlinLeastSquares.NoProgressException(Object[]) - Constructor for exception com.imsl.math.NonlinLeastSquares.NoProgressException
 
NonlinLeastSquares.TooManyIterationsException - Exception in com.imsl.math
Too many iterations.
NonlinLeastSquares.TooManyIterationsException() - Constructor for exception com.imsl.math.NonlinLeastSquares.TooManyIterationsException
 
NonlinLeastSquares.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.math.NonlinLeastSquares.TooManyIterationsException
 
NonlinLeastSquares.TooManyIterationsException(Object[]) - Constructor for exception com.imsl.math.NonlinLeastSquares.TooManyIterationsException
 
NonNegativeLeastSquares - Class in com.imsl.math
Solves a linear least squares problem with nonnegativity constraints.
NonNegativeLeastSquares(double[][], double[]) - Constructor for class com.imsl.math.NonNegativeLeastSquares
Construct a new NonNegativeLeastSquares instance to solve Ax-b where x is a vector of n unknowns.
NonNegativeLeastSquares.TooManyIterException - Exception in com.imsl.math
Maximum number of iterations has been exceeded.
NonNegativeLeastSquares.TooManyIterException(String) - Constructor for exception com.imsl.math.NonNegativeLeastSquares.TooManyIterException
The maximum number of iterations has been exceeded.
NonNegativeLeastSquares.TooManyIterException(String, Object[]) - Constructor for exception com.imsl.math.NonNegativeLeastSquares.TooManyIterException
The maximum number of iterations has been exceeded.
NonNegativeLeastSquares.TooMuchTimeException - Exception in com.imsl.math
Maximum time allowed for solve is exceeded.
NonNegativeLeastSquares.TooMuchTimeException(String) - Constructor for exception com.imsl.math.NonNegativeLeastSquares.TooMuchTimeException
The maximum time allowed for solve is exceeded.
NonNegativeLeastSquares.TooMuchTimeException(String, Object[]) - Constructor for exception com.imsl.math.NonNegativeLeastSquares.TooMuchTimeException
The maximum time allowed for solve is exceeded.
norm(double[]) - Method in interface com.imsl.math.GenMinRes.Norm
Used to compute the norm Vert X Vert in the Gram-Schmidt implementation.
normal(double) - Static method in class com.imsl.stat.Cdf
Evaluates the normal (Gaussian) cumulative probability distribution function.
normal(double) - Static method in class com.imsl.stat.InvCdf
Evaluates the inverse of the normal (Gaussian) cumulative probability distribution function.
normal(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the normal (Gaussian) probability density function.
NormalDistribution - Class in com.imsl.stat
Evaluates the normal (Gaussian) probability density for a given set of data.
NormalDistribution() - Constructor for class com.imsl.stat.NormalDistribution
 
NormalityTest - Class in com.imsl.stat
Performs a test for normality.
NormalityTest(double[]) - Constructor for class com.imsl.stat.NormalityTest
Constructor for NormalityTest.
NormalityTest.NoVariationInputException - Exception in com.imsl.stat
There is no variation in the input data.
NormalityTest.NoVariationInputException(String) - Constructor for exception com.imsl.stat.NormalityTest.NoVariationInputException
 
NormalityTest.NoVariationInputException(String, Object[]) - Constructor for exception com.imsl.stat.NormalityTest.NoVariationInputException
 
NormOneSample - Class in com.imsl.stat
Computes statistics for mean and variance inferences using a sample from a normal population.
NormOneSample(double[]) - Constructor for class com.imsl.stat.NormOneSample
Constructor to compute statistics for mean and variance inferences using a sample from a normal population.
NormTwoSample - Class in com.imsl.stat
Computes statistics for mean and variance inferences using samples from two normal populations.
NormTwoSample(double[], double[]) - Constructor for class com.imsl.stat.NormTwoSample
Constructor to compute statistics for mean and variance inferences using samples from two normal populations.
NOT_A_KNOT - Static variable in class com.imsl.math.CsInterpolate
 
NpChart - Class in com.imsl.chart.qc
NpChart is an np-chart for monitoring the number of defects when defects are not rare.
NpChart(AxisXY, int, int[]) - Constructor for class com.imsl.chart.qc.NpChart
Creates an np-Chart given the number of defects in a series of samples.
NpChart(AxisXY, int[], int[]) - Constructor for class com.imsl.chart.qc.NpChart
Creates a np-Chart given the number of defects in a series of samples, where the number of observations per sample is not constant.
nper(double, double, double, double, int) - Static method in class com.imsl.finance.Finance
Returns the number of periods for an investment for which periodic, and constant payments are made and the interest rate is constant.
npv(double, double[]) - Static method in class com.imsl.finance.Finance
Returns the net present value of a stream of equal periodic cash flows, which are subject to a given discount rate.
numberFormat - Variable in class com.imsl.math.PrintMatrixFormat
The NumberFormat to be used in formatting double and Complex entries.
numberOfColumns - Variable in class com.imsl.math.ComplexSparseMatrix.SparseArray
Number of columns in the matrix.
numberOfColumns - Variable in class com.imsl.math.SparseMatrix.SparseArray
Number of columns in the matrix.
numberOfNonZeros - Variable in class com.imsl.math.ComplexSparseMatrix.SparseArray
Number of nonzeros in the matrix.
numberOfNonZeros - Variable in class com.imsl.math.SparseMatrix.SparseArray
Number of nonzeros in the matrix.
numberOfRows - Variable in class com.imsl.math.ComplexSparseMatrix.SparseArray
Number of rows in the matrix.
numberOfRows - Variable in class com.imsl.math.SparseMatrix.SparseArray
Number of rows in the matrix.
NumericalDerivatives - Class in com.imsl.math
Compute the Jacobian matrix for a function f(y) with m components in n independent variables.
NumericalDerivatives(NumericalDerivatives.Function) - Constructor for class com.imsl.math.NumericalDerivatives
Constructor for NumericalDerivatives.
NumericalDerivatives.Function - Interface in com.imsl.math
Public interface function.
NumericalDerivatives.Jacobian - Interface in com.imsl.math
Public interface for the user-supplied function to compute the Jacobian.
nY - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.GradObjective
 
nY - Variable in class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective
 

O

ODE - Class in com.imsl.math
ODE represents and solves an initial-value problem for ordinary differential equations.
ODE() - Constructor for class com.imsl.math.ODE
 
OdeAdamsGear - Class in com.imsl.math
Extension of the ODE class to solve a stiff initial-value problem for ordinary differential equations using the Adams-Gear methods.
OdeAdamsGear(OdeAdamsGear.Function) - Constructor for class com.imsl.math.OdeAdamsGear
Constructs an ODE solver to solve the initial value problem dy/dt = f(t,y)
OdeAdamsGear.DidNotConvergeException - Exception in com.imsl.math
The iteration did not converge within the maximum number of steps allowed (default 500).
OdeAdamsGear.DidNotConvergeException(String) - Constructor for exception com.imsl.math.OdeAdamsGear.DidNotConvergeException
Constructs a DidNotConvergeException with the specified detailed message.
OdeAdamsGear.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.math.OdeAdamsGear.DidNotConvergeException
Constructs a DidNotConvergeException with the specified detailed message.
OdeAdamsGear.Function - Interface in com.imsl.math
Public interface for user supplied function to OdeAdamsGear object.
OdeAdamsGear.Jacobian - Interface in com.imsl.math
Public interface for the user supplied function to evaluate the Jacobian matrix.
OdeAdamsGear.MaxFcnEvalsExceededException - Exception in com.imsl.math
Maximum function evaluations exceeded.
OdeAdamsGear.MaxFcnEvalsExceededException(String) - Constructor for exception com.imsl.math.OdeAdamsGear.MaxFcnEvalsExceededException
Constructs a MaxFcnEvalsExceededException with the specified detailed message.
OdeAdamsGear.MaxFcnEvalsExceededException(String, Object[]) - Constructor for exception com.imsl.math.OdeAdamsGear.MaxFcnEvalsExceededException
Constructs a MaxFcnEvalsExceededException with the specified detailed message.
OdeAdamsGear.SingularMatrixException - Exception in com.imsl.math
The interpolation matrix is singular.
OdeAdamsGear.SingularMatrixException(String) - Constructor for exception com.imsl.math.OdeAdamsGear.SingularMatrixException
Constructs a SingularMatrixException with the specified detailed message.
OdeAdamsGear.SingularMatrixException(String, Object[]) - Constructor for exception com.imsl.math.OdeAdamsGear.SingularMatrixException
Constructs a SingularMatrixException with the specified detailed message.
OdeAdamsGear.ToleranceTooSmallException - Exception in com.imsl.math
Tolerance is too small or the problem is stiff.
OdeAdamsGear.ToleranceTooSmallException(String) - Constructor for exception com.imsl.math.OdeAdamsGear.ToleranceTooSmallException
Constructs a ToleranceTooSmallException with the specified detailed message.
OdeAdamsGear.ToleranceTooSmallException(String, Object[]) - Constructor for exception com.imsl.math.OdeAdamsGear.ToleranceTooSmallException
Constructs a ToleranceTooSmallException with the specified detailed message.
OdeRungeKutta - Class in com.imsl.math
Solves an initial-value problem for ordinary differential equations using the Runge-Kutta-Verner fifth-order and sixth-order method.
OdeRungeKutta(OdeRungeKutta.Function) - Constructor for class com.imsl.math.OdeRungeKutta
Constructs an ODE solver to solve the initial value problem dy/dt = f(t,y)
OdeRungeKutta.DidNotConvergeException - Exception in com.imsl.math
The iteration did not converge within the maximum number of steps allowed (default 500).
OdeRungeKutta.DidNotConvergeException(String) - Constructor for exception com.imsl.math.OdeRungeKutta.DidNotConvergeException
Constructs a DidNotConvergeException with the specified detailed message.
OdeRungeKutta.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.math.OdeRungeKutta.DidNotConvergeException
Constructs a DidNotConvergeException with the specified detailed message.
OdeRungeKutta.Function - Interface in com.imsl.math
Public interface for user supplied function to OdeRungeKutta object.
OdeRungeKutta.ToleranceTooSmallException - Exception in com.imsl.math
Tolerance is too small or the problem is stiff.
OdeRungeKutta.ToleranceTooSmallException(String) - Constructor for exception com.imsl.math.OdeRungeKutta.ToleranceTooSmallException
Constructs a ToleranceTooSmallException with the specified detailed message.
OdeRungeKutta.ToleranceTooSmallException(String, Object[]) - Constructor for exception com.imsl.math.OdeRungeKutta.ToleranceTooSmallException
Constructs a ToleranceTooSmallException with the specified detailed message.
ONE_AT_A_TIME - Static variable in class com.imsl.stat.ANOVA
The One-at-a-Time (Fisher's LSD) method
ONE_SIDED - Static variable in class com.imsl.math.NumericalDerivatives
Indicates one sided differences.
oneNorm(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Return the Complex matrix one norm.
oneNorm() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the matrix one norm of the sparse matrix.
oneNorm(double[][]) - Static method in class com.imsl.math.Matrix
Return the matrix one norm.
oneNorm() - Method in class com.imsl.math.SparseMatrix
Returns the matrix one norm of the sparse matrix.
order - Variable in class com.imsl.math.BSpline
Order of the spline.
out - Variable in class com.imsl.WarningObject
The warning stream.
outline - Static variable in class com.imsl.chart.Draw
Markers defined on a [-1,1] x [-1,1] grid.
OutputLayer - Class in com.imsl.datamining.neural
Output layer in a neural network.
OutputPerceptron - Class in com.imsl.datamining.neural
A Perceptron in the OutputLayer.

P

paint(Draw) - Method in class com.imsl.chart.Annotation
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Axis
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Axis1D
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisLabel
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisLine
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisR
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisRLabel
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisRLine
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisRMajorTick
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisTheta
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisTitle
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisUnit
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.AxisXY
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Background
Paint this node.
paint(Draw) - Method in class com.imsl.chart.Bar
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.BarItem
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.BarSet
 
paint(Draw) - Method in class com.imsl.chart.BoxPlot
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Candlestick
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.CandlestickItem
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Chart
Paints this node and all of its children.
paint(Graphics) - Method in class com.imsl.chart.Chart
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.ChartNode
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.ChartTitle
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Contour.Legend
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Contour
 
paint(Draw) - Method in class com.imsl.chart.ContourLevel
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Data
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Dendrogram
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.ErrorBar
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Grid
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.GridPolar
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Heatmap.Legend
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Heatmap
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.HighLowClose
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Legend
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.MajorTick
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.MinorTick
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.PieSlice
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Polar
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.qc.ControlLimit
Paints the horizontal control limit line as wide as the window.
paint(Draw) - Method in class com.imsl.chart.qc.ShewhartControlChart
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.ToolTip
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Treemap.Legend
Paints this node and all of its children.
paint(Draw) - Method in class com.imsl.chart.Treemap
Paints this node and all of its children.
paint(Graphics) - Method in class com.imsl.chart3d.BufferedPaint
Paint the image onto the canvas.
paint(Graphics) - Method in class com.imsl.chart3d.Canvas3DChart
Paint method overriden to correct a problem in JDK 1.4.
paint(Graphics) - Method in interface com.imsl.chart3d.Canvas3DChart.Paint
 
paintChart(Graphics) - Method in class com.imsl.chart.Chart
Draw the chart using the given Graphics object.
paintComponent(Graphics) - Method in class com.imsl.chart.JPanelChart
Calls the UI delegate's paint method, if the UI delegate is non-null.
paintImage() - Method in class com.imsl.chart.Chart
Returns an Image of the chart.
PANEL_SIZE - Static variable in class com.imsl.math.ComplexSuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
PANEL_SIZE - Static variable in class com.imsl.math.SuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
Pareto(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the Pareto cumulative probability distribution function.
Pareto(double, double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the Pareto cumulative probability density function.
Pareto(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the Pareto probability density function.
ParetoChart - Class in com.imsl.chart.qc
ParetoChart is a Pareto bar chart.
ParetoChart(AxisXY, String[], int[]) - Constructor for class com.imsl.chart.qc.ParetoChart
Constructs a Pareto chart.
ParetoChart(AxisXY, String[], int[], double, String) - Constructor for class com.imsl.chart.qc.ParetoChart
Constructs a Pareto chart showing only the most important bars.
ParetoChart(AxisXY, String[], int[], int, String) - Constructor for class com.imsl.chart.qc.ParetoChart
Constructs a Pareto chart showing only a limited number of bars.
parse(String) - Method in interface com.imsl.io.FlatFile.Parser
Parse a String into an Object.
parse(String) - Method in class com.imsl.io.Tokenizer
Sets the line to be tokenized.
PARSE_BYTE - Static variable in class com.imsl.io.FlatFile
Implements a Parser that converts a String to a Byte.
PARSE_DOUBLE - Static variable in class com.imsl.io.FlatFile
Implements a Parser that converts a String to a Double.
PARSE_FLOAT - Static variable in class com.imsl.io.FlatFile
Implements a Parser that converts a String to a Float.
PARSE_INTEGER - Static variable in class com.imsl.io.FlatFile
Implements a Parser that converts a String to a Integer.
PARSE_LONG - Static variable in class com.imsl.io.FlatFile
Implements a Parser that converts a String to a Long.
PARSE_SHORT - Static variable in class com.imsl.io.FlatFile
Implements a Parser that converts a String to a Short.
parseColor(String) - Static method in class com.imsl.chart.AbstractChartNode
Returns a color specified by name or a red-green-blue triple.
PartialCovariances - Class in com.imsl.stat
Class PartialCovariances computes the partial covariances or partial correlations from an input covariance or correlation matrix.
PartialCovariances(int, double[][], int) - Constructor for class com.imsl.stat.PartialCovariances
Creates a PartialCovariances object from a covariance or correleation matrix with a the independent variables in the initial columns and the dependent variables in the final columns.
PartialCovariances(int[], double[][], int) - Constructor for class com.imsl.stat.PartialCovariances
Creates a PartialCovariances object from a covariance or correleation matrix with a mix of dependent and independent variables.
PartialCovariances.InvalidMatrixException - Exception in com.imsl.stat
Exception thrown if a computed correlation is greater than one for some pair of variables.
PartialCovariances.InvalidMatrixException(int, int) - Constructor for exception com.imsl.stat.PartialCovariances.InvalidMatrixException
Creates an InvalidMatrixException thrown if a computed correlation is greater than one for some pair of variables.
PartialCovariances.InvalidPartialCorrelationException - Exception in com.imsl.stat
Exception thrown if a computed partial correlation is greater than one for some pair of variables.
PartialCovariances.InvalidPartialCorrelationException(int, int) - Constructor for exception com.imsl.stat.PartialCovariances.InvalidPartialCorrelationException
Creates an InvalidPartialCorrelationException thrown if a computed partial correlation is greater than one for some pair of variables.
path - Variable in class com.imsl.chart.Draw
 
PChart - Class in com.imsl.chart.qc
PChart is a p-chart for monitoring the defect rate when defects are not rare.
PChart(AxisXY, int, double[]) - Constructor for class com.imsl.chart.qc.PChart
Creates a p-Chart given the defect rates for a series of samples with equal sample sizes.
PChart(AxisXY, int[], double[]) - Constructor for class com.imsl.chart.qc.PChart
Creates a p-Chart given the defect rates for a series of samples with varying sample sizes.
PChart(AxisXY, int, int[]) - Constructor for class com.imsl.chart.qc.PChart
Creates a p-Chart given the number of defects for a series of samples with equal sample sizes.
PChart(AxisXY, int[], int[]) - Constructor for class com.imsl.chart.qc.PChart
Creates a p-Chart given the number of defects for a series of samples with varying sample sizes.
Pdf - Class in com.imsl.stat
Probability density functions.
Pdf.AltSeriesAccuracyLossException - Exception in com.imsl.stat
The magnitude of alternating series sum is too small relative to the sum of positive terms to permit a reliable accuracy.
Pdf.AltSeriesAccuracyLossException(String) - Constructor for exception com.imsl.stat.Pdf.AltSeriesAccuracyLossException
The magnitude of alternating series sum is too small relative to the sum of positive terms to permit a reliable accuracy.
Pdf.AltSeriesAccuracyLossException(String, Object[]) - Constructor for exception com.imsl.stat.Pdf.AltSeriesAccuracyLossException
The magnitude of alternating series sum is too small relative to the sum of positive terms to permit a reliable accuracy.
Perceptron - Class in com.imsl.datamining.neural
A Perceptron node in a neural network.
performanceIndex(double[][]) - Method in class com.imsl.math.Eigen
Returns the performance index of a real eigensystem.
performanceIndex(double[][]) - Method in class com.imsl.math.SymEigen
Returns the performance index of a real symmetric eigensystem.
Physical - Class in com.imsl.math
Return the value of various mathematical and physical constants.
Physical() - Constructor for class com.imsl.math.Physical
Constructs a new 0-valued, dimensionless object.
Physical(Physical) - Constructor for class com.imsl.math.Physical
Constructs a copy of a Physical object.
Physical(double, String) - Constructor for class com.imsl.math.Physical
Constructs a new Physical object and initializes this object to a double value.
Physical(double, int, int, int, int, int) - Constructor for class com.imsl.math.Physical
Constructs a new Physical object and initializes this object to a double value along with int values for length, mass, time, current, and temperature.
PI - Static variable in class com.imsl.math.JMath
 
pick(MouseEvent) - Method in class com.imsl.chart.Chart
Fire the PickListeners for the nodes hit by the event.
PickEvent - Class in com.imsl.chart
An event that indicates that a chart element has been selected.
PickEvent(MouseEvent) - Constructor for class com.imsl.chart.PickEvent
Construct a PickEvent object.
PickEvent(Component, int, long, int, int, int, int, boolean) - Constructor for class com.imsl.chart.PickEvent
Construct a PickEvent object at point (x,y).
PickListener - Interface in com.imsl.chart
The listener interface for receiving pick events.
pickNode() - Method in class com.imsl.chart.DrawPick
Register the currentNode as the "picked" node if the "PickListener" attribute is defined for the current node.
pickPerformed(PickEvent) - Method in interface com.imsl.chart.PickListener
Public interface for PickListener.
pickPerformed(PickEvent) - Method in class com.imsl.chart.ToolTip
Part of the PickListener interface.
Pie - Class in com.imsl.chart
A pie chart.
Pie(Chart) - Constructor for class com.imsl.chart.Pie
Constructs a Pie chart object.
Pie(Chart, double[]) - Constructor for class com.imsl.chart.Pie
Constructs a Pie chart object with a specified number of slices.
PieSlice - Class in com.imsl.chart
One wedge of a pie chart.
plusEquals(int, int, Complex) - Method in class com.imsl.math.ComplexSparseMatrix
Adds a value to an element in the matrix.
plusEquals(int, int, double) - Method in class com.imsl.math.SparseMatrix
Adds a value to an element in the matrix.
pmt(double, int, double, double, int) - Static method in class com.imsl.finance.Finance
Returns the periodic payment for an investment.
poch(double, double) - Static method in class com.imsl.math.Sfun
Returns a generalization of Pochhammer's symbol.
PointLight - Class in com.imsl.chart3d
A point light source.
PointLight(Chart3D) - Constructor for class com.imsl.chart3d.PointLight
Creates a point light source at the origin.
PointLight(Chart3D, double, double, double) - Constructor for class com.imsl.chart3d.PointLight
Creates a point light at a specified position.
pointToLine(int, int, int[], int[]) - Static method in class com.imsl.chart.PickEvent
Compute the distance from the point (Px,Py) to the line segment AB.
poisson(int, double) - Static method in class com.imsl.stat.Cdf
Evaluates the Poisson cumulative probability distribution function.
poisson(int, double) - Static method in class com.imsl.stat.Pdf
Evaluates the Poisson probability density function.
PoissonDistribution - Class in com.imsl.stat
Evaluates a Poisson probability density of a given set of data.
PoissonDistribution() - Constructor for class com.imsl.stat.PoissonDistribution
 
Polar - Class in com.imsl.chart
This Axis node is used for polar charts.
Polar(Chart) - Constructor for class com.imsl.chart.Polar
Create an AxisPolar.
poly(int[], int[]) - Method in class com.imsl.chart.DrawMap
Sets a polygon as the target.
POOL_INTERACTIONS - Static variable in class com.imsl.stat.ANOVAFactorial
Indicates factor nSubscripts is not error.
POOLED - Static variable in class com.imsl.stat.DiscriminantAnalysis
Indicates pooled covariances computation.
POOLED_GROUP - Static variable in class com.imsl.stat.DiscriminantAnalysis
Indicates pooled, group covariances computation.
postRender() - Method in class com.imsl.chart3d.Canvas3DChart
Calls the Paint objects added to the post-render list.
postSwap() - Method in class com.imsl.chart3d.Canvas3DChart
Writes the chart to a file as a bitmap image.
pow(Complex, double) - Static method in class com.imsl.math.Complex
Returns the Complex z raised to the x power, with a branch cut for the first parameter (z) along the negative real axis.
pow(Complex, Complex) - Static method in class com.imsl.math.Complex
Returns the Complex x raised to the Complex y power.
pow(double, double) - Static method in class com.imsl.math.JMath
Returns x to the power y.
ppmt(double, int, int, double, double, int) - Static method in class com.imsl.finance.Finance
Returns the payment on the principal for a specified period.
preconditioner(double[], double[]) - Method in interface com.imsl.math.ConjugateGradient.Preconditioner
Used to compute z = M^{-1}r where M is the preconditioning matrix and r and z are arrays of length n, the order of matrix M.
preconditioner(double[], double[]) - Method in interface com.imsl.math.GenMinRes.Preconditioner
Used to compute z = M^{-1}r where M is the preconditioning matrix and r and z are arrays of length n, the order of matrix M.
predictClass(double[], int[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Predicts the classification for the input pattern using the trained Naive Bayes classifier.
predictedClass(double[]) - Method in class com.imsl.datamining.neural.BinaryClassification
Calculates the classification probablities for the input pattern x, and returns either 0 or 1 identifying the class with the highest probability.
predictedClass(double[]) - Method in class com.imsl.datamining.neural.MultiClassification
Calculates the classification probablities for the input pattern x, and returns the class with the highest probability.
prePaint() - Method in class com.imsl.chart.ChartNode
The prePaint method is called in all nodes in a chart just before the chart is painted.
prePaint() - Method in class com.imsl.chart.qc.CChart
Setup chart with current settings.
prePaint() - Method in class com.imsl.chart.qc.CuSum
 
prePaint() - Method in class com.imsl.chart.qc.CuSumStatus
Setup chart with current settings.
prePaint() - Method in class com.imsl.chart.qc.EWMA
Setup chart with current settings.
prePaint() - Method in class com.imsl.chart.qc.NpChart
Setup chart with current settings.
prePaint() - Method in class com.imsl.chart.qc.PChart
Setup chart with current settings.
prePaint() - Method in class com.imsl.chart.qc.RChart
Setup chart with current settings.
prePaint() - Method in class com.imsl.chart.qc.SChart
Setup chart with current settings.
prePaint() - Method in class com.imsl.chart.qc.UChart
Setup chart with current settings.
prePaint() - Method in class com.imsl.chart.qc.XbarR
Setup chart with current settings.
prePaint() - Method in class com.imsl.chart.qc.XbarS
Setup chart with current settings.
prePaint() - Method in class com.imsl.chart.qc.XmR
Setup chart with current settings.
preRender() - Method in class com.imsl.chart3d.Canvas3DChart
Calls the Paint objects added to the pre-render list.
previous() - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor to the previous row in this ResultSet object.
price(GregorianCalendar, GregorianCalendar, double, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the price, per $100 face value, of a security that pays periodic interest.
pricedisc(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the price of a discount bond given the discount rate.
pricemat(GregorianCalendar, GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the price, per $100 face value, of a discount bond.
priceyield(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the price of a discount bond given the yield.
PRINCIPAL_COMPONENT_MODEL - Static variable in class com.imsl.stat.FactorAnalysis
Indicates principal component model.
PRINCIPAL_FACTOR_MODEL - Static variable in class com.imsl.stat.FactorAnalysis
Indicates principal factor model.
print(Graphics, PageFormat, int) - Method in class com.imsl.chart.Chart
This method implements the Printable interface.
print() - Method in class com.imsl.chart.JPanelChart
Print the chart, centered on a page.
print() - Method in class com.imsl.chart.qc.CuSumStatus
Prints the tabular CuSum results.
print(String) - Method in class com.imsl.math.PrintMatrix
Print a string.
print(Object) - Method in class com.imsl.math.PrintMatrix
Prints an nRows by nColumns matrix with specified format.
print(PrintMatrixFormat, Object) - Method in class com.imsl.math.PrintMatrix
Prints an nRows by nColumns matrix with specified format.
print(Object, String, String, Object[]) - Static method in class com.imsl.Warning
Issue a warning message.
print(Object, String, String, Object[]) - Method in class com.imsl.WarningObject
Issue a warning message.
printHTML(PrintMatrixFormat, Object, int, int) - Method in class com.imsl.math.PrintMatrix
Prints an nRows by nColumns matrix with specified format for HTML output.
println() - Method in class com.imsl.math.PrintMatrix
Print a newline.
PrintMatrix - Class in com.imsl.math
Matrix printing utilities.
PrintMatrix() - Constructor for class com.imsl.math.PrintMatrix
Creates an instance of the PrintMatrix class.
PrintMatrix(PrintStream) - Constructor for class com.imsl.math.PrintMatrix
Creates an instance of the PrintMatrix class with the specified PrintStream.
PrintMatrix(String) - Constructor for class com.imsl.math.PrintMatrix
Creates a PrintMatrix object and sets its title.
PrintMatrix(PrintStream, String) - Constructor for class com.imsl.math.PrintMatrix
Creates a PrintMatrix object with the specified PrintStream and sets its title.
PrintMatrixFormat - Class in com.imsl.math
This class can be used to customize the actions of PrintMatrix.
PrintMatrixFormat() - Constructor for class com.imsl.math.PrintMatrixFormat
Constructs a PrintMatrixFormat object.
PRIOR_EQUAL - Static variable in class com.imsl.stat.DiscriminantAnalysis
Indicates prior equal probabilities.
PRIOR_PROPORTIONAL - Static variable in class com.imsl.stat.DiscriminantAnalysis
Indicates prior proportional probabilities.
PRISM - Static variable in interface com.imsl.chart.Colormap
Prism colormap.
probabilities(double[], int[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Predicts the classification probabilities for the input pattern using the trained Naive Bayes classifier.
probabilities(double[]) - Method in class com.imsl.datamining.neural.BinaryClassification
Returns classification probabilities for the input pattern x.
probabilities(double[]) - Method in class com.imsl.datamining.neural.MultiClassification
Returns classification probabilities for the input pattern x.
ProbabilityDistribution - Interface in com.imsl.stat
Public interface for a user-supplied probability distribution.
processCommand(String, String) - Method in class com.imsl.io.MPSReader
Process a section of the MPS file.
ProportionalHazards - Class in com.imsl.stat
Analyzes survival and reliability data using Cox's proportional hazards model.
ProportionalHazards(double[][], int[], int[]) - Constructor for class com.imsl.stat.ProportionalHazards
Constructor for ProportionalHazards.
ProportionalHazards.ClassificationVariableLimitException - Exception in com.imsl.stat
The Classification Variable limit set by the user through setUpperBound has been exceeded.
ProportionalHazards.ClassificationVariableLimitException(String) - Constructor for exception com.imsl.stat.ProportionalHazards.ClassificationVariableLimitException
Constructs a ClassificationVariableLimitException.
ProportionalHazards.ClassificationVariableLimitException(String, Object[]) - Constructor for exception com.imsl.stat.ProportionalHazards.ClassificationVariableLimitException
The Classification Variable limit set by the user through setUpperBound has been exceeded.
psi(double) - Static method in class com.imsl.math.Sfun
Returns the derivative of the log gamma function, also called the digamma function.
psi1(double) - Static method in class com.imsl.math.Sfun
Returns the psi _1 function, also known as the trigamma function.
PURE_ERROR - Static variable in class com.imsl.stat.ANOVAFactorial
Indicates factor nSubscripts is error.
pv(double, int, double, double, int) - Static method in class com.imsl.finance.Finance
Returns the net present value of a stream of equal periodic cash flows, which are subject to a given discount rate.

Q

QR - Class in com.imsl.math
QR Decomposition of a matrix.
QR(double[][]) - Constructor for class com.imsl.math.QR
Constructs the QR decomposition of a matrix with elements of type double.
QUADRATIC - Static variable in class com.imsl.stat.DiscriminantAnalysis
Indicates a quadratic discrimination method.
QuadraticProgramming - Class in com.imsl.math
Solves the convex quadratic programming problem subject to equality or inequality constraints.
QuadraticProgramming(double[][], double[], double[][], double[], double[][], double[]) - Constructor for class com.imsl.math.QuadraticProgramming
Solve a quadratic programming problem.
QuadraticProgramming.InconsistentSystemException - Exception in com.imsl.math
The system of constraints is inconsistent.
QuadraticProgramming.InconsistentSystemException() - Constructor for exception com.imsl.math.QuadraticProgramming.InconsistentSystemException
The system of constraints is inconsistent.
QuadraticProgramming.InconsistentSystemException(String) - Constructor for exception com.imsl.math.QuadraticProgramming.InconsistentSystemException
 
QuadraticProgramming.NoLPSolutionException - Exception in com.imsl.math
No solution for the LP problem with h = 0 was found by DenseLP.
QuadraticProgramming.NoLPSolutionException() - Constructor for exception com.imsl.math.QuadraticProgramming.NoLPSolutionException
No solution for the LP problem with h = 0 was found by DenseLP.
QuadraticProgramming.NoLPSolutionException(String) - Constructor for exception com.imsl.math.QuadraticProgramming.NoLPSolutionException
No solution for the LP problem with h = 0 was found by DenseLP.
QuadraticProgramming.NoLPSolutionException(String, Object[]) - Constructor for exception com.imsl.math.QuadraticProgramming.NoLPSolutionException
No solution for the LP problem with h = 0 was found by DenseLP.
QuadraticProgramming.ProblemUnboundedException - Exception in com.imsl.math
The object value for the problem is unbounded.
QuadraticProgramming.ProblemUnboundedException() - Constructor for exception com.imsl.math.QuadraticProgramming.ProblemUnboundedException
The object value for the problem is unbounded.
QuadraticProgramming.ProblemUnboundedException(String) - Constructor for exception com.imsl.math.QuadraticProgramming.ProblemUnboundedException
The object value for the problem is unbounded.
QuadraticProgramming.SolutionNotFoundException - Exception in com.imsl.math
A solution was not found.
QuadraticProgramming.SolutionNotFoundException() - Constructor for exception com.imsl.math.QuadraticProgramming.SolutionNotFoundException
A solution was not found.
QuadraticProgramming.SolutionNotFoundException(String) - Constructor for exception com.imsl.math.QuadraticProgramming.SolutionNotFoundException
A solution was not found.
Quadrature - Class in com.imsl.math
Quadrature is a general-purpose integrator that uses a globally adaptive scheme in order to reduce the absolute error.
Quadrature() - Constructor for class com.imsl.math.Quadrature
Constructs a Quadrature object.
Quadrature.Function - Interface in com.imsl.math
Public interface function for the Quadrature class.
QUARTERLY - Static variable in class com.imsl.finance.Bond
Coupon payments are made quarterly.
QuasiNewtonTrainer - Class in com.imsl.datamining.neural
Trains a network using the quasi-Newton method, MinUnconMultiVar.
QuasiNewtonTrainer() - Constructor for class com.imsl.datamining.neural.QuasiNewtonTrainer
Constructs a QuasiNewtonTrainer object.
QuasiNewtonTrainer.BlockGradObjective - Class in com.imsl.datamining.neural
 
QuasiNewtonTrainer.BlockGradObjective() - Constructor for class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockGradObjective
 
QuasiNewtonTrainer.BlockObjective - Class in com.imsl.datamining.neural
 
QuasiNewtonTrainer.BlockObjective() - Constructor for class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockObjective
 
QuasiNewtonTrainer.Error - Interface in com.imsl.datamining.neural
Error function to be minimized by trainer.
QuasiNewtonTrainer.GradObjective - Class in com.imsl.datamining.neural
The Objective class is passed to the optimizer.
QuasiNewtonTrainer.Objective - Class in com.imsl.datamining.neural
The Objective class is passed to the optimizer.

R

R_SQUARED_CRITERION - Static variable in class com.imsl.stat.SelectionRegression
Indicates R^2 criterion regression.
RadialBasis - Class in com.imsl.math
RadialBasis computes a least-squares fit to scattered data in {bf R}^d, where d is the dimension.
RadialBasis(int, int) - Constructor for class com.imsl.math.RadialBasis
Creates a new instance of RadialBasis.
RadialBasis.Function - Interface in com.imsl.math
Public interface for the user supplied function to the RadialBasis object.
RadialBasis.Gaussian - Class in com.imsl.math
The Gaussian basis function, e^{-ax^2}.
RadialBasis.Gaussian(double) - Constructor for class com.imsl.math.RadialBasis.Gaussian
Creates a Gaussian basis function e^{-ax^2}.
RadialBasis.HardyMultiquadric - Class in com.imsl.math
The Hardy multiquadric basis function, sqrt{r^2+delta^2}.
RadialBasis.HardyMultiquadric(double) - Constructor for class com.imsl.math.RadialBasis.HardyMultiquadric
Creates a Hardy multiquadric basis function sqrt{r^2+
 delta^2}.
RADIAN - Static variable in class com.imsl.chart.Draw
 
random() - Static method in class com.imsl.math.JMath
Returns a random number from a uniform distribution.
Random - Class in com.imsl.stat
Generate uniform and non-uniform random number distributions.
Random() - Constructor for class com.imsl.stat.Random
Constructor for the Random number generator class.
Random(long) - Constructor for class com.imsl.stat.Random
Constructor for the Random number generator class with supplied seed.
Random(Random.BaseGenerator) - Constructor for class com.imsl.stat.Random
Constructor for the Random number generator class with an alternate basic number generator.
Random.BaseGenerator - Interface in com.imsl.stat
Base pseudorandom number.
RandomSequence - Interface in com.imsl.stat
Interface implemented by generators of random or quasi-random multidimension sequences.
RANGE - Static variable in class com.imsl.stat.Dissimilarities
Indicates scaling by the range.
rank(double) - Method in class com.imsl.math.QR
Returns the rank of the matrix given an input tolerance.
Ranks - Class in com.imsl.stat
Compute the ranks, normal scores, or exponential scores for a vector of observations.
Ranks() - Constructor for class com.imsl.stat.Ranks
Constructor for the Ranks class.
rate(int, double, double, double, int) - Static method in class com.imsl.finance.Finance
Returns the interest rate per period of an annuity.
rate(int, double, double, double, int, double) - Static method in class com.imsl.finance.Finance
Returns the interest rate per period of an annuity with an initial guess.
Rayleigh(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the Rayleigh cumulative probability distribution function.
Rayleigh(double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the Rayleigh cumulative probability distribution function.
Rayleigh(double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the Rayleigh probability density function.
RChart - Class in com.imsl.chart.qc
RChart is an R chart using sample ranges to monitor the variability of a process.
RChart(AxisXY, double[][]) - Constructor for class com.imsl.chart.qc.RChart
Creates an R chart given sample data.
RChart(AxisXY, int, double[]) - Constructor for class com.imsl.chart.qc.RChart
Creates an R chart given the ranges for a series of equally sized samples.
RChart(AxisXY, int[], double[]) - Constructor for class com.imsl.chart.qc.RChart
Creates an R chart given the means for a series of equally sized samples.
read(Reader) - Method in class com.imsl.io.MPSReader
Reads and parses the MPS file.
readLine() - Method in class com.imsl.io.FlatFile
Reads and returns a line from the input.
real() - Method in class com.imsl.math.Complex
Returns the real part of a Complex object.
real(Complex) - Static method in class com.imsl.math.Complex
Returns the real part of a Complex object.
received(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the amount one receives when a fully invested security reaches the maturity date.
RECIPROCAL_ABS - Static variable in class com.imsl.stat.ClusterHierarchical
Indicates transformation by taking the reciprocal of the absolute value.
RECLASSIFICATION - Static variable in class com.imsl.stat.DiscriminantAnalysis
Indicates reclassification classification method.
rect(int, int, int, int) - Method in class com.imsl.chart.DrawMap
Sets a rectangle as the target.
RED - Static variable in interface com.imsl.chart.Colormap
Linear red colormap.
RED_PURPLE - Static variable in interface com.imsl.chart.Colormap
Red/purple colormap.
RED_TEMPERATURE - Static variable in interface com.imsl.chart.Colormap
Red temperature colormap.
refreshRow() - Method in class com.imsl.io.AbstractFlatFile
Refreshes the current row with its most recent value in the database.
registerChart(Chart, HttpServletRequest) - Method in class com.imsl.chart.JspBean
Saves the chart and sets the chart attribute "Size".
RegressionBasis - Interface in com.imsl.stat
Public interface for user supplied function to UserBasisRegression object.
RegressorsForGLM - Class in com.imsl.stat
Generates regressors for a general linear model.
RegressorsForGLM(double[][], int) - Constructor for class com.imsl.stat.RegressorsForGLM
Constructor where the class columns are the first columns.
RegressorsForGLM(double[][], int[]) - Constructor for class com.imsl.stat.RegressorsForGLM
Constructor with an explicit set of class column indicies.
relative(int) - Method in class com.imsl.io.AbstractFlatFile
Moves the cursor a relative number of rows, either positive or negative.
RELAXATION_PARAMETER - Static variable in class com.imsl.math.ComplexSuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
RELAXATION_PARAMETER - Static variable in class com.imsl.math.SuperLU
A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
remove() - Method in class com.imsl.chart.AbstractChartNode
Removes the node from its parents list of children.
remove() - Method in class com.imsl.chart3d.ColormapLegend
Removes the node from its parents list of children.
remove(Link) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Removes a Link from the network.
removeControlLimit(ControlLimit) - Method in class com.imsl.chart.qc.ShewhartControlChart
Removes a control limit from the chart.
removePickListener(PickListener) - Method in class com.imsl.chart.ChartNode
Removes a PickListener from this node.
removePostRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart
Removes a Paint object from the list of post-render Paint objects.
removePreRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart
Removes a Paint object from the list of pre-render Paint objects.
render() - Method in class com.imsl.chart3d.Canvas3DChart
Creates a scene graph from the chart tree and starts rendering the scene graph into this canvas.
render() - Method in class com.imsl.chart3d.JFrameChart3D
Renders the 3D chart node tree into a Java 3D scene graph.
repaint() - Method in class com.imsl.chart.Chart
Prepares the chart to be repainted by deleting any double buffering image.
resetQ() - Method in class com.imsl.stat.KalmanFilter
Removes the Q matrix.
resetTransitionMatrix() - Method in class com.imsl.stat.KalmanFilter
Removes the transition matrix.
resetUpdate() - Method in class com.imsl.stat.KalmanFilter
Do not perform computation of the update equations.
resetViewPlatformTransformation() - Method in class com.imsl.chart3d.Chart3D
Resets the view platform transformation to its default value.
rightBoundaries(double, double[][]) - Method in interface com.imsl.math.FeynmanKac.Boundaries
Returns the coefficient values of the right boundary conditions.
rint(double) - Static method in class com.imsl.math.JMath
Returns the value of a double rounded toward the closest integral value.
round(float) - Static method in class com.imsl.math.JMath
Returns the integer closest to a given float.
round(double) - Static method in class com.imsl.math.JMath
Returns the long closest to a given double.
ROW_AND_COLUMN_SCALING - Static variable in class com.imsl.math.ComplexSuperLU
Indicates that input matrix A was row and column scaled before factorization.
ROW_AND_COLUMN_SCALING - Static variable in class com.imsl.math.SuperLU
Indicates that input matrix A was row and column scaled before factorization.
ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat
This flag as the type argument to format, indicates that the formatted string for a given row label is to be returned.
ROW_SCALING - Static variable in class com.imsl.math.ComplexSuperLU
Indicates that input matrix A was row scaled before factorization.
ROW_SCALING - Static variable in class com.imsl.math.SuperLU
Indicates that input matrix A was row scaled before factorization.
rowDeleted() - Method in class com.imsl.io.AbstractFlatFile
Indicates whether a row has been deleted.
ROWFIRST - Static variable in class com.imsl.chart.Treemap
Flag to set the treemap orientation drawing rows first.
rowInserted() - Method in class com.imsl.io.AbstractFlatFile
Indicates whether the current row has had an insertion.
rowUpdated() - Method in class com.imsl.io.AbstractFlatFile
Indicates whether the current row has been updated.

S

sampleStandardDeviation(double[]) - Static method in class com.imsl.stat.Summary
Returns the sample standard deviation of the given data set.
sampleStandardDeviation(double[], double[]) - Static method in class com.imsl.stat.Summary
Returns the sample standard deviation of the given data set and associated weights.
sampleVariance(double[]) - Static method in class com.imsl.stat.Summary
Returns the sample variance of the given data set.
sampleVariance(double[], double[]) - Static method in class com.imsl.stat.Summary
Returns the sample variance of the given data set and associated weights.
saveChart(Chart, HttpServletRequest) - Method in class com.imsl.chart.JspBean
Saves the chart so that a servlet can later render it.
scalbn(double, int) - Static method in class com.imsl.math.IEEE
Returns 2n computed by exponent manipulation rather than by actually performing an exponentiation or a multiplication.
scaledK(double, double, int) - Static method in class com.imsl.math.Bessel
Evaluate a sequence of exponentially scaled modified Bessel functions of the third kind with fractional order and real argument.
ScaleFilter - Class in com.imsl.datamining.neural
Scales or unscales continuous data prior to its use in neural network training, testing, or forecasting.
ScaleFilter(int) - Constructor for class com.imsl.datamining.neural.ScaleFilter
Constructor for ScaleFilter.
scaleFont - Variable in class com.imsl.chart.Draw
 
SChart - Class in com.imsl.chart.qc
SChart is an S chart using sample standard deviations to monitor the variability of a process.
SChart(AxisXY, double[][]) - Constructor for class com.imsl.chart.qc.SChart
Creates an S chart given sample data.
SChart(AxisXY, int, double[]) - Constructor for class com.imsl.chart.qc.SChart
Creates an S chart given the within sample standard deviations for a series of equally sized samples.
SChart(AxisXY, int[], double[]) - Constructor for class com.imsl.chart.qc.SChart
Creates an S chart given the within sample standard deviations for a series of unequally sized samples.
SCHEFFE - Static variable in class com.imsl.stat.ANOVA
The Scheffe method
SECOND_DERIVATIVE - Static variable in class com.imsl.math.CsInterpolate
 
SECOND_GRAM_SCHMIDT - Static variable in class com.imsl.math.GenMinRes
Indicates the second Gram-Schmidt implementation method is to be used.
SECOND_HOUSEHOLDER - Static variable in class com.imsl.math.GenMinRes
Indicates the second Householder implementation method is to be used.
SelectionRegression - Class in com.imsl.stat
Selects the best multiple linear regression models.
SelectionRegression(int) - Constructor for class com.imsl.stat.SelectionRegression
Constructs a new SelectionRegression object.
SelectionRegression.NoVariablesException - Exception in com.imsl.stat
No Variables can enter the model.
SelectionRegression.NoVariablesException() - Constructor for exception com.imsl.stat.SelectionRegression.NoVariablesException
Constructs a NoVariablesException.
SelectionRegression.Statistics - Class in com.imsl.stat
Statistics contains statistics related to the regression coefficients.
SEMIANNUAL - Static variable in class com.imsl.finance.Bond
Coupon payments are made semiannually (twice per year).
serialVersionUID - Static variable in interface com.imsl.datamining.neural.Activation
 
set(int, int, Complex) - Method in class com.imsl.math.ComplexSparseMatrix
Sets the value of an element in the matrix.
set(int, int, double) - Method in class com.imsl.math.SparseMatrix
Sets the value of an element in the matrix.
setAbsoluteError(double) - Method in class com.imsl.math.HyperRectangleQuadrature
Sets the absolute error tolerance.
setAbsoluteError(double) - Method in class com.imsl.math.Quadrature
Sets the absolute error tolerance.
setAbsoluteError(double) - Method in class com.imsl.math.ZerosFunction
Sets the second convergence criterion.
setAbsoluteErrorTolerances(double[]) - Method in class com.imsl.math.FeynmanKac
Sets the absolute error tolerances.
setAbsoluteErrorTolerances(double) - Method in class com.imsl.math.FeynmanKac
Sets the absolute error tolerances.
setAbsoluteFcnTol(double) - Method in class com.imsl.math.BoundedLeastSquares
Sets the absolute function tolerance.
setAbsoluteH(double) - Method in class com.imsl.chart.qc.CuSumStatus
Sets the value for h used for setting limits.
setAbsoluteTolerance(double) - Method in class com.imsl.math.NonlinLeastSquares
Set the absolute function tolerance.
setAbsoluteTolerance(double) - Method in class com.imsl.stat.NonlinearRegression
Sets the absolute function tolerance.
setAccuracy(double) - Method in class com.imsl.math.MinUncon
Set the required absolute accuracy in the final value returned by member function computeMin.
setAccuracyTolerance(double) - Method in class com.imsl.stat.ARMAOutlierIdentification
Sets the tolerance value controlling the accuracy of the parameter estimates.
setAccuracyTolerance(double) - Method in class com.imsl.stat.AutoARIMA
Sets the tolerance value controlling the accuracy of the parameter estimates.
setActivation(Activation) - Method in class com.imsl.datamining.neural.Perceptron
Sets the activation function.
setAlignment(int) - Method in class com.imsl.chart.Text
Sets the alignment for this Text object.
setAlpha(double) - Method in class com.imsl.stat.MultipleComparisons
Sets the significance level of the test
setALT(String) - Method in class com.imsl.chart.ChartNode
Sets the value of the "ALT" attribute.
setAngles(double, double) - Method in class com.imsl.chart.PieSlice
Sets the angles, in degrees, that determine the extent of this slice.
setAR(double[]) - Method in class com.imsl.stat.ARMAMaxLikelihood
Sets the initial values for the autoregressive terms to the p values in ar.
setARLags(int[]) - Method in class com.imsl.stat.ARMA
Sets the order of the autoregressive parameters.
setArmaInfo(double, double[], double[], double) - Method in class com.imsl.stat.ARMA
Sets the ARMA_Info Object to previously determined values
setAttribute(String, Object) - Method in class com.imsl.chart.AbstractChartNode
Sets an attribute.
setAutoscaleInput(int) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "AutoscaleInput" attribute.
setAutoscaleMinimumTimeInterval(int) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "AutoscaleMinimumTimeInterval" attribute.
setAutoscaleOutput(int) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "AutoscaleOutput" attribute.
setAxisRange(double[]) - Method in class com.imsl.chart.Treemap
Set the axis range, range = {xmin,xmax,ymin,ymax}.
setAxisTitlePosition(int) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "AxisTitlePosition" attribute.
setBackcasting(int, double) - Method in class com.imsl.stat.ARMA
Sets backcasting option.
setBackwardOrigin(int) - Method in class com.imsl.stat.ARAutoUnivariate
Sets the maximum backward origin used in calculating the forecasts.
setBackwardOrigin(int) - Method in class com.imsl.stat.ARMA
Sets the maximum backward origin.
setBackwardOrigin(int) - Method in class com.imsl.stat.ARMAMaxLikelihood
Sets the maximum backward origin.
setBarData(double[][][]) - Method in class com.imsl.chart.Bar
Convenience routine to set the "BarData" attribute.
setBarGap(double) - Method in class com.imsl.chart.ChartNode
Sets the value of the "BarGap" attribute.
setBarType(int) - Method in class com.imsl.chart.ChartNode
Sets the value of the "BarType" attribute.
setBarWidth(double) - Method in class com.imsl.chart.ChartNode
Sets the value of the "BarWidth" attribute.
setBias(double) - Method in class com.imsl.datamining.neural.Perceptron
Sets the bias for this Perceptron.
setBias(double[]) - Method in class com.imsl.math.CsTCB
Sets the bias values at the data points.
setBindingThreshold(double) - Method in class com.imsl.math.MinConNLP
Set the binding threshold for constraints.
setBound(double) - Method in class com.imsl.math.MinUncon
Set the amount by which X may be changed from its initial value, xguess.
setBoundingSphere(BoundingSphere) - Method in class com.imsl.chart3d.ChartNode3D
Sets the spherical bounding region object BoundingSphere.
setBounds(double, double, double, double) - Method in class com.imsl.datamining.neural.ScaleFilter
Sets bounds to be used during bounded scaling and unscaling.
setBounds(double, double) - Method in class com.imsl.math.ZerosFunction
Sets the closed interval in which to search for the roots.
setBoundViolationBound(double) - Method in class com.imsl.math.MinConNLP
Set the amount by which bounds may be violated during numerical differentiation.
setBoxPlotType(int) - Method in class com.imsl.chart.BoxPlot
Sets the "BoxPlotType" attribute value.
setCanvas(Canvas3D) - Method in class com.imsl.chart3d.Chart3D
 
setCensor(int[]) - Method in class com.imsl.stat.KaplanMeierECDF
Set flags to note right-censoring
setCensorColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel
Sets the column number in x which contains the interval type for each observation.
setCensorColumn(int) - Method in class com.imsl.stat.KaplanMeierEstimates
Sets the column index of x containing the optional censoring code for each observation.
setCensorColumn(int) - Method in class com.imsl.stat.ProportionalHazards
Sets the column index of x containing the optional censoring code for each observation.
setCenter(double) - Method in class com.imsl.chart.qc.ShewhartControlChart
Sets the value of the attribute "Center".
setCenter(double) - Method in class com.imsl.datamining.neural.ScaleFilter
Set the measure of center to be used during z-score scaling.
setCenter(boolean) - Method in class com.imsl.stat.ARMA
Sets center option.
setCenter(int) - Method in class com.imsl.stat.ARSeasonalFit
Controls centering of the differenced series.
setChart(Chart) - Method in class com.imsl.chart.JFrameChart
Sets the chart to be handled.
setChart(Chart) - Method in class com.imsl.chart.JPanelChart
Sets the Chart to be handled by this container.
setChartServletName(String) - Method in class com.imsl.chart.JspBean
Sets the URL of the servlet used to render the chart.
setChartTitle(ChartTitle) - Method in class com.imsl.chart.ChartNode
Sets the value of the "ChartTitle" attribute.
setChiSquaredTestNull(double) - Method in class com.imsl.stat.NormOneSample
Sets the null hypothesis value for the chi-squared test.
setChiSquaredTestNull(double) - Method in class com.imsl.stat.NormTwoSample
Sets the null hypothesis value for the chi-squared test.
setClassificationMethod(int) - Method in class com.imsl.stat.DiscriminantAnalysis
Specifies the classification method to be either reclassification or leave-out-one.
setClassificationVariableColumn(int[]) - Method in class com.imsl.stat.CategoricalGenLinModel
Initializes an index vector to contain the column numbers in x that are classification variables.
setClassVarColumns(int[]) - Method in class com.imsl.stat.ProportionalHazards
Sets the column indices of x that are the classification variables.
setClip(Rectangle) - Method in class com.imsl.chart.Draw
Set the clipping rectangle.
setClipData(boolean) - Method in class com.imsl.chart.ChartNode
Sets the value of the "ClipData" attribute.
setClose(double[]) - Method in class com.imsl.chart.HighLowClose
Sets the attribute "Close".
setColorFunction(ColorFunction) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "ColorFunction" attribute.
setColormap(Colormap) - Method in class com.imsl.chart.Heatmap
Sets the value of the "Colormap" attribute.
setColormap(Colormap) - Method in class com.imsl.chart.Treemap
Sets the value of the "Colormap" attribute.
setColumnClass(int, Class) - Method in class com.imsl.io.AbstractFlatFile
Sets a column class.
setColumnClass(int, Class) - Method in class com.imsl.io.FlatFile
 
setColumnLabels(String[]) - Method in class com.imsl.math.PrintMatrixFormat
Turns on column labeling using the given labels.
setColumnName(int, String) - Method in class com.imsl.io.AbstractFlatFile
Sets a column name.
setColumnParser(int, FlatFile.Parser) - Method in class com.imsl.io.FlatFile
Sets the Parser for the specified column.
setColumnPermutationMethod(int) - Method in class com.imsl.math.ComplexSuperLU
Specifies how to permute the columns of the input matrix.
setColumnPermutationMethod(int) - Method in class com.imsl.math.SuperLU
Specifies how to permute the columns of the input matrix.
setColumnSpacing(int) - Method in class com.imsl.math.PrintMatrix
Sets the number of spaces between columns.
setComponent(Component) - Method in class com.imsl.chart.Chart
Sets the Component for this chart.
setConfidence(double) - Method in class com.imsl.stat.ARAutoUnivariate
Sets the confidence level for calculating confidence limit deviations returned from getDeviations.
setConfidence(double) - Method in class com.imsl.stat.ARMA
Sets the confidence level for calculating confidence limit deviations returned from getDeviations.
setConfidence(double) - Method in class com.imsl.stat.ARMAMaxLikelihood
Sets the confidence level for calculating confidence limit deviations returned from getDeviations().
setConfidence(double) - Method in class com.imsl.stat.ARMAOutlierIdentification
Sets the confidence level for calculating confidence limit deviations returned from getDeviations.
setConfidence(double) - Method in class com.imsl.stat.AutoARIMA
Sets the confidence level for calculating confidence limit deviations returned by getDeviations.
setConfidenceMean(double) - Method in class com.imsl.stat.NormOneSample
Sets the confidence level (in percent) for a two-sided interval estimate of the mean.
setConfidenceMean(double) - Method in class com.imsl.stat.NormTwoSample
Sets the confidence level (in percent) for a two-sided interval estimate of the mean of x - the mean of y, in percent.
setConfidenceVariance(double) - Method in class com.imsl.stat.NormOneSample
Sets the confidence level (in percent) for two-sided interval estimate of the variances.
setConfidenceVariance(double) - Method in class com.imsl.stat.NormTwoSample
Sets the confidence level (in percent) for two-sided interval estimate of the variances.
setConLevelMean(double) - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Sets the confidence level for two-sided interval estimates on the mean, in percent.
setConLevelPred(double) - Method in class com.imsl.stat.LinearRegression.CaseStatistics
Sets the confidence level for two-sided prediction intervals, in percent.
setConstant(double) - Method in class com.imsl.stat.ARMAMaxLikelihood
Sets the initial value for the constant term in the ARMA model.
setConstantColumn(int) - Method in class com.imsl.stat.ProportionalHazards
Sets the column index of x containing the constant w_i to be added to the linear response.
setConstraintType(int[]) - Method in class com.imsl.math.DenseLP
Sets the types of general constraints in the matrix a.
setContinuity(double[]) - Method in class com.imsl.math.CsTCB
Sets the continuity values at the data points.
setContinuousSmoothingValue(double) - Method in class com.imsl.datamining.NaiveBayesClassifier
Parameter for calculating smoothed estimates of conditional probabilities for continuous attributes.
setControlLimit(double) - Method in class com.imsl.chart.qc.ControlLimit
Sets the attribute "ControlLimit".
setConvergenceCriterion1(double) - Method in class com.imsl.stat.FactorAnalysis
Sets the convergence criterion used to terminate the iterations.
setConvergenceCriterion2(double) - Method in class com.imsl.stat.FactorAnalysis
Sets the convergence criterion used to switch to exact second derivatives.
setConvergenceTol(double) - Method in class com.imsl.stat.ProportionalHazards
Set the convergence tolerance.
setConvergenceTolerance(double) - Method in class com.imsl.stat.ARAutoUnivariate
Sets the tolerance level used to determine convergence of the nonlinear least-squares and maximum likelihood algorithms.
setConvergenceTolerance(double) - Method in class com.imsl.stat.ARMA
Sets the tolerance level used to determine convergence of the nonlinear least-squares algorithm.
setConvergenceTolerance(double) - Method in class com.imsl.stat.ARMAEstimateMissing
Sets the covergence tolerance used by the AR_1 and AR_P missing value estimation methods.
setConvergenceTolerance(double) - Method in class com.imsl.stat.CategoricalGenLinModel
Set the convergence criterion.
setCoordinates(double[][]) - Method in class com.imsl.chart.Dendrogram
Convenience routine to set the "Coordinates" attribute.
setCovarianceComputation(int) - Method in class com.imsl.stat.DiscriminantAnalysis
Specifies the covariance matrix computation to be either pooled or pooled, group.
setCreateImageMap(boolean) - Method in class com.imsl.chart.JspBean
Sets a flag indicating if a client-size imagemap is to be generated.
setCriterionOption(int) - Method in class com.imsl.stat.SelectionRegression
Sets the Criterion to be used.
setCriticalValue(double) - Method in class com.imsl.stat.ARMAOutlierIdentification
Sets the critical value used as a threshold during outlier detection.
setCriticalValue(double) - Method in class com.imsl.stat.AutoARIMA
Sets the critical value used as a threshold during outlier detection.
setCross(double, double) - Method in class com.imsl.chart.AxisXY
Sets the value of the "Cross" attribute.
setCross(double[]) - Method in class com.imsl.chart.AxisXY
Sets the value of the "Cross" attribute.
setCustomMarker(Data.CustomMarkerFactory) - Method in class com.imsl.chart3d.Data
Sets a custom marker factory.
setCustomTransform(Transform) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "CustomTransform" attribute.
setCustomTransform(Transform) - Method in class com.imsl.chart.ChartNode
Sets the value of the "CustomTransform" attribute.
setCutpoints(double[]) - Method in class com.imsl.stat.ChiSquaredTest
Sets the cutpoints.
setData(double[]) - Method in class com.imsl.chart.Pie
Changes the data in a Pie chart object.
setData(int[]) - Method in class com.imsl.chart.qc.ShewhartControlChart
Sets the integer data in the control chart.
setData(double[]) - Method in class com.imsl.chart.qc.ShewhartControlChart
Sets the data in the control chart.
setDataType(int) - Method in class com.imsl.chart.ChartNode
Sets the value of the "DataType" attribute.
setDataType(int) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "DataType" attribute.
setDateAxis(String) - Method in class com.imsl.chart.HighLowClose
Sets up the x-axis for high-low-close plot.
setDateColumnParser(int, String, Locale) - Method in class com.imsl.io.FlatFile
Creates for a pattern string and sets the Parser for the specified column.
setDefaultAlignment(int) - Method in class com.imsl.chart.Text
Sets the alignment to use, if it has not been set using setAlignment(int).
setDefaultOffset(double) - Method in class com.imsl.chart.Text
Sets the default value of the offset.
setDegreesOfFreedom(int) - Method in class com.imsl.stat.FactorAnalysis
Sets the number of degrees of freedom.
setDelta(double) - Method in class com.imsl.stat.ARMAOutlierIdentification
Sets the dampening effect parameter.
setDelta(double) - Method in class com.imsl.stat.AutoARIMA
Sets the dampening effect parameter.
setDensity(int) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "Density" attribute.
setDerivtol(double) - Method in class com.imsl.math.MinUncon
Set the derivative tolerance used by member function computeMin to decide if the current point is a local minimum.
setDiagonalPivotThreshold(double) - Method in class com.imsl.math.ComplexSuperLU
Specifies the threshold used for a diagonal entry to be an acceptable pivot.
setDiagonalPivotThreshold(double) - Method in class com.imsl.math.SuperLU
Specifies the threshold used for a diagonal entry to be an acceptable pivot.
setDiagonalScalingMatrix(double[]) - Method in class com.imsl.math.BoundedLeastSquares
Sets the diagonal scaling matrix for the functions.
setDifferenceOrders(int[]) - Method in class com.imsl.stat.AutoARIMA
Defines the orders of the periodic differences used in the determination of the optimum model.
setDifferencingMethods(int[]) - Method in class com.imsl.math.NumericalDerivatives
Sets the methods used to compute the derivatives
setDifferentiationType(int) - Method in class com.imsl.math.MinConNLP
Set the type of numerical differentiation to be used.
setDigits(double) - Method in class com.imsl.math.MinUnconMultiVar
Set the number of good digits in the function.
setDigits(int) - Method in class com.imsl.math.NonlinLeastSquares
Set the number of good digits in the function.
setDigits(int) - Method in class com.imsl.stat.NonlinearRegression
Sets the number of good digits in the residuals.
setDInitial(int[][]) - Method in class com.imsl.stat.ARSeasonalFit
Sets the candidate values for selecting the optimum seasonal adjustment prior to calling the compute method.
setDirection(double, double, double) - Method in class com.imsl.chart3d.DirectionalLight
Sets the value of the "Direction" attribute to a light direction.
setDirection(Vector3f) - Method in class com.imsl.chart3d.DirectionalLight
Sets the value of the "Direction" attribute to a light direction.
setDiscreteSmoothingValue(double) - Method in class com.imsl.datamining.NaiveBayesClassifier
Parameter for calculating smoothed estimates of conditional probabilities for discrete (nominal) attributes.
setDiscriminationMethod(int) - Method in class com.imsl.stat.DiscriminantAnalysis
Specifies the discrimination method used to be either linear or quadratic discrimination.
setDistanceMethod(int) - Method in class com.imsl.stat.Dissimilarities
Sets the method to be used in computing the dissimilarities or similarities.
setDoubleBuffering(boolean) - Method in class com.imsl.chart.ChartNode
Sets the value of the "DoubleBuffering" attribute.
setDualTolerance(double) - Method in class com.imsl.math.NonNegativeLeastSquares
Sets the dual tolerance.
setDummyMethod(int) - Method in class com.imsl.stat.RegressorsForGLM
Sets the dummy method.
setEffects(int[], int[]) - Method in class com.imsl.stat.CategoricalGenLinModel
Initializes an index vector to contain the column numbers in x associated with each effect.
setEffects(int[][]) - Method in class com.imsl.stat.RegressorsForGLM
Set the effects.
setEpochNumber(int) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Sets the epoch number for the trainer.
setEpochNumber(int) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Sets the epoch number for the trainer.
setEpochSize(int) - Method in class com.imsl.datamining.neural.EpochTrainer
Sets the number of randomly selected training patterns in stage 1 epoch.
setEqualColumnWidths(boolean) - Method in class com.imsl.math.PrintMatrix
Force all of the columns to have the same width.
setEqualWeights(double[][]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Initializes network weights using equal weighting.
setEquilibrate(boolean) - Method in class com.imsl.math.ComplexSuperLU
Specifies if input matrix A should be equilibrated before factorization.
setEquilibrate(boolean) - Method in class com.imsl.math.SuperLU
Determines if input matrix A should be equilibrated before factorization.
setError(QuasiNewtonTrainer.Error) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Sets the function used to compute the network error.
setError(double) - Method in class com.imsl.math.ZerosFunction
Sets the first convergence criterion.
setErrorIncludeType(int) - Method in class com.imsl.stat.ANOVAFactorial
Sets error included type.
setEstimationMethod(int) - Method in class com.imsl.stat.ARAutoUnivariate
Sets the estimation method used for estimating the final estimates for the autoregressive coefficients.
setEstimationMethod(int) - Method in class com.imsl.stat.ARMAEstimateMissing
Sets the method used for estimating the autoregressive coefficients for missing value estimation methods AR_1 and AR_P.
setExclude(boolean) - Method in class com.imsl.stat.ARSeasonalFit
Controls whether to exclude or replace the inital values in the transformed series.
setExpectedMean(double) - Method in class com.imsl.chart.qc.CuSum
Sets the expected mean of all of the data from all of the samples.
setExpectedMean(double) - Method in class com.imsl.chart.qc.CuSumStatus
Sets the expected mean of all of the data from all of the samples.
setExplode(double) - Method in class com.imsl.chart.ChartNode
Sets the value of the "Explode" attribute.
setExtendedLikelihoodObservations(int[]) - Method in class com.imsl.stat.CategoricalGenLinModel
Initializes a vector indicating which observations are to be included in the extended likelihood.
setExtrapolation(boolean) - Method in class com.imsl.math.Quadrature
If true, the epsilon-algorithm for extrapolation is enabled.
setFactorLoadingEstimationMethod(int) - Method in class com.imsl.stat.FactorAnalysis
Sets the factor loading estimation method.
setFalseConvergenceTolerance(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Set the false convergence tolerance.
setFalseConvergenceTolerance(double) - Method in class com.imsl.math.NonlinLeastSquares
Set the false convergence tolerance.
setFalseConvergenceTolerance(double) - Method in class com.imsl.stat.NonlinearRegression
Sets the false convergence tolerance.
setFetchDirection(int) - Method in class com.imsl.io.AbstractFlatFile
Gives a hint as to the direction in which the rows in this ResultSet object will be processed.
setFetchSize(int) - Method in class com.imsl.io.AbstractFlatFile
Gives the JDBC driver a hint as to the number of rows that should be fetched from the database when more rows are needed for this ResultSet object.
setFillColor(Color) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "FillColor" attribute.
setFillColor(String) - Method in class com.imsl.chart.AbstractChartNode
Sets the "FillColor" attribute to a color specified by name.
setFillOutlineColor(Color) - Method in class com.imsl.chart.ChartNode
Sets the value of the "FillOutlineColor" attribute.
setFillOutlineColor(String) - Method in class com.imsl.chart.ChartNode
Sets the value of the "FillOutlineColor" attribute to a color specified by name.
setFillOutlineType(int) - Method in class com.imsl.chart.ChartNode
Sets the value of the "FillOutlineType" attribute.
setFillPaint(Paint) - Method in class com.imsl.chart.ChartNode
Sets the value of the "FillPaint" attribute.
setFillPaint(ImageIcon) - Method in class com.imsl.chart.ChartNode
Sets the value of the "FillPaint" attribute.
setFillPaint(URL) - Method in class com.imsl.chart.ChartNode
Sets the value of the "FillPaint" attribute.
setFillType(int) - Method in class com.imsl.chart.ChartNode
Sets the value of the "FillType" attribute.
setFirstColumnNumber(int) - Method in class com.imsl.math.PrintMatrixFormat
Turns on column labeling with index numbers and sets the index for the label of the first column.
setFirstRowNumber(int) - Method in class com.imsl.math.PrintMatrixFormat
Turns on row labeling with index numbers and sets the index for the label of the first row.
setFirstTick(double) - Method in class com.imsl.chart.Axis1D
Convenience routine to set the "FirstTick" attribute.
setFirstTick(double) - Method in class com.imsl.chart3d.Axis3D
Convenience routine to set the "FirstTick" attribute.
setFixedParameterColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel
Sets the column number in x that contains a fixed parameter for each observation that is added to the linear response prior to computing the model parameter.
setFloor(double) - Method in class com.imsl.math.ODE
Sets the value used in the norm computation.
setFont(Font) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the font attributes.
setFontName(String) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "FontName" attribute.
setFontSize(int) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "FontSize" attribute.
setFontStyle(int) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "FontStyle" attribute.
setForce(int) - Method in class com.imsl.stat.StepwiseRegression
Forces independent variables into the model based on their level assigned from setlevels.
setForcingTerm(FeynmanKac.ForcingTerm) - Method in class com.imsl.math.FeynmanKac
Sets the user-supplied method that computes approximations to the forcing term phi(x) and its derivative partial phi/partial y used in the FeynmanKac PDE.
setFrequencies(double[]) - Method in class com.imsl.stat.ClusterKMeans
Sets the frequency for each observation.
setFrequencies(double[]) - Method in class com.imsl.stat.Covariances
Sets the frequency for each observation.
setFrequencies(double[]) - Method in class com.imsl.stat.TableMultiWay
 
setFrequency(int[]) - Method in class com.imsl.stat.KaplanMeierECDF
Sets the frequency for each entry in t
setFrequencyColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel
Sets the column number in x that contains the frequency of response for each observation.
setFrequencyColumn(int) - Method in class com.imsl.stat.KaplanMeierEstimates
Sets the column index of x containing the frequency of response for each observation.
setFrequencyColumn(int) - Method in class com.imsl.stat.ProportionalHazards
Sets the column index of x containing the frequency of response for each observation.
setFscale(double) - Method in class com.imsl.math.MinUnconMultiVar
Set the function scaling value for scaling the gradient.
setFscale(double[]) - Method in class com.imsl.math.NonlinLeastSquares
Set the diagonal scaling matrix for the functions.
setFunctionPrecision(double) - Method in class com.imsl.math.MinConNLP
Set the relative precision of the function evaluation routine.
setFuzz(double) - Method in class com.imsl.stat.Ranks
Sets the fuzz factor used in determining ties.
setFuzz(double) - Method in class com.imsl.stat.WilcoxonRankSum
Sets the nonnegative constant used to determine ties in computing ranks in the combined samples.
setGaussLegendreDegree(int) - Method in class com.imsl.math.FeynmanKac
Sets the number of quadrature points used in the Gauss-Legendre quadrature formula.
setGoodDigit(int) - Method in class com.imsl.math.BoundedLeastSquares
Sets the number of good digits in the function.
setGradient(Color, Color, Color, Color) - Method in class com.imsl.chart.ChartNode
Sets the value of the "Gradient" attribute.
setGradient(String, String, String, String) - Method in class com.imsl.chart.ChartNode
Sets the value of the "Gradient" attribute using named colors.
setGradient(Color[]) - Method in class com.imsl.chart.ChartNode
Sets the value of the "Gradient" attribute.
setGradientPrecision(double) - Method in class com.imsl.math.MinConNLP
Set the relative precision in gradients.
setGradientTol(double) - Method in class com.imsl.math.BoundedLeastSquares
Sets the scaled gradient tolerance.
setGradientTolerance(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Set the gradient tolerance.
setGradientTolerance(double) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Set the gradient tolerance.
setGradientTolerance(double) - Method in class com.imsl.math.MinUnconMultiVar
Sets the gradient tolerance.
setGradientTolerance(double) - Method in class com.imsl.math.NonlinLeastSquares
Set the scaled gradient tolerance stopping critierion.
setGradientTolerance(double) - Method in class com.imsl.stat.ARMAMaxLikelihood
Sets the tolerance for the convergence algorithm.
setGradientTolerance(double) - Method in class com.imsl.stat.NonlinearRegression
Sets the gradient tolerance used to compute the gradient.
setGuess(double[]) - Method in class com.imsl.math.BoundedLeastSquares
Sets the initial guess of the solution.
setGuess(double[]) - Method in class com.imsl.math.GenMinRes
Set the initial guess of the solution.
setGuess(double[]) - Method in class com.imsl.math.MinConGenLin
Sets an initial guess of the solution.
setGuess(double[]) - Method in class com.imsl.math.MinConNLP
Set the initial guess of the minimum point of the input function.
setGuess(double) - Method in class com.imsl.math.MinUncon
Set the initial guess of the minimum point of the input function.
setGuess(double[]) - Method in class com.imsl.math.MinUnconMultiVar
Set the initial guess of the minimum point of the input function.
setGuess(double[]) - Method in class com.imsl.math.NonlinLeastSquares
Set the initial guess of the minimum point of the input function.
setGuess(double[]) - Method in class com.imsl.math.NonNegativeLeastSquares
Sets the initial guess.
setGuess(double[]) - Method in class com.imsl.math.ZerosFunction
Sets the initial guess for the zeros.
setGuess(double[]) - Method in class com.imsl.math.ZeroSystem
Sets the initial estimate of the root.
setGuess(double[]) - Method in class com.imsl.stat.NonlinearRegression
Sets the initial guess of the parameter values
setHeatmapLabels(String[][]) - Method in class com.imsl.chart.Heatmap
Sets the value of the "HeatmapLabels" attribute.
setHeatmapLabels(Text[][]) - Method in class com.imsl.chart.Heatmap
Sets the value of the "HeatmapLabels" attribute.
setHessianOption(boolean) - Method in class com.imsl.stat.ProportionalHazards
Set the option to have the Hessian and gradient be computed at the initial estimates.
setHigh(double[]) - Method in class com.imsl.chart.ErrorBar
Convenience routine to set the "High" attribute.
setHigh(double[]) - Method in class com.imsl.chart.HighLowClose
Convenience routine to set the "High" attribute.
setHREF(String) - Method in class com.imsl.chart.ChartNode
Sets the value of the "HREF" attribute.
setIhess(int) - Method in class com.imsl.math.MinUnconMultiVar
Set the Hessian initialization parameter.
setImage(ImageIcon) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "Image" attribute.
setImage(Image) - Method in class com.imsl.chart.ChartNode
Sets the value of the "Image" attribute.
setIndex(int[]) - Method in class com.imsl.stat.Dissimilarities
Sets the indices of the rows (columns).
setInfiniteEstimateMethod(int) - Method in class com.imsl.stat.CategoricalGenLinModel
Sets the method to be used for handling infinite estimates.
setInitialCMinus(double) - Method in class com.imsl.chart.qc.CuSumStatus
Sets the initial value of C^{-}.
setInitialCPlus(double) - Method in class com.imsl.chart.qc.CuSumStatus
Sets the initial value of C^{+}.
setInitialData(FeynmanKac.InitialData) - Method in class com.imsl.math.FeynmanKac
Sets the user-supplied method for adjustment of initial data or as an opportunity for output during the integration steps.
setInitialEstimates(double[], double[]) - Method in class com.imsl.stat.ARMA
Sets preliminary estimates for the LEAST_SQUARES estimation method.
setInitialEstimates(int, double[]) - Method in class com.imsl.stat.CategoricalGenLinModel
Sets the initial parameter estimates option.
setInitialEstimates(double[]) - Method in class com.imsl.stat.ProportionalHazards
Sets the initial parameter estimates.
setInitialF(double[]) - Method in class com.imsl.math.NumericalDerivatives
Set the initial function values.
setInitialStepsize(double) - Method in class com.imsl.math.FeynmanKac
Sets the starting stepsize for the integration.
setInitialStepsize(double) - Method in class com.imsl.math.ODE
Sets the initial internal step size.
setInitialTrustRegion(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Sets the intial trust region.
setInitialTrustRegion(double) - Method in class com.imsl.math.NonlinLeastSquares
Set the initial trust region radius.
setInitialTrustRegion(double) - Method in class com.imsl.stat.NonlinearRegression
Sets the initial trust region radius.
setIntegrationMethod(int) - Method in class com.imsl.math.OdeAdamsGear
Indicates which integration method is to be used.
setInternalScale() - Method in class com.imsl.math.BoundedLeastSquares
Sets the internal variable scaling option.
setIterativeRefinement(boolean) - Method in class com.imsl.math.ComplexSuperLU
Specifies whether to perform iterative refinement.
setIterativeRefinement(boolean) - Method in class com.imsl.math.SuperLU
Specifies whether to perform iterative refinement.
setJacobi(double[]) - Method in class com.imsl.math.ConjugateGradient
Defines a Jacobi preconditioner as the preconditioning matrix, that is, M is the diagonal of A.
setJacobian(BoundedLeastSquares.Jacobian) - Method in class com.imsl.math.BoundedLeastSquares
Sets the Jacobian.
setKeyboard(boolean) - Method in class com.imsl.chart3d.Chart3D
Sets the value of the "Keyboard" attribute.
setLabels(String[]) - Method in class com.imsl.chart.AxisLabel
Sets the axis label values for this node to be used instead of the default numbers.
setLabels(String[]) - Method in class com.imsl.chart.AxisRLabel
Sets the axis label values for this node to be used instead of the default numbers.
setLabels(String[], int) - Method in class com.imsl.chart.Bar
Sets up an axis with bar labels.
setLabels(String[]) - Method in class com.imsl.chart.Bar
Sets up an axis with bar labels.
setLabels(String[], int) - Method in class com.imsl.chart.BoxPlot
Sets up an axis with labels.
setLabels(String[]) - Method in class com.imsl.chart.BoxPlot
Sets up an axis with labels.
setLabels(String[]) - Method in class com.imsl.chart.Dendrogram
Sets up the axis labels for dendrogram plot.
setLabels(String[]) - Method in class com.imsl.chart.Treemap
Sets the value of the "TreemapLabels" attribute.
setLabels(Text[]) - Method in class com.imsl.chart.Treemap
Sets the value of the "TreemapLabels" attribute.
setLabels(String[]) - Method in class com.imsl.chart3d.AxisLabel
Sets the axis label values for this node to be used instead of the default numbers.
setLabelType(int) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "LabelType" attribute.
setLambda(double) - Method in class com.imsl.chart.qc.EWMA
Sets the value of the attribute "Lambda".
setLeftEndTangent(double) - Method in class com.imsl.math.CsTCB
Sets the value of the tangent at the left endpoint.
setLeftSons(int[]) - Method in class com.imsl.chart.Dendrogram
Convenience routine to set the "LeftSons" attribute.
setLevels(double[]) - Method in class com.imsl.chart.Dendrogram
Convenience routine to set the "Levels" attribute.
setLevels(int[]) - Method in class com.imsl.stat.StepwiseRegression
Sets the levels of priority for variables entering and leaving the regression.
setLightColor(Color) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "LightColor" attribute.
setLightColor(String) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "LightColor" attribute to a color specified by name.
setLightingEnabled(boolean) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "LightingEnabled" attribute.
setLineColor(Color) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "LineColor" attribute.
setLineColor(String) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "LineColor" attribute.
setLineColor(String[]) - Method in class com.imsl.chart.Dendrogram
Define colors for individual clusters.
setLineColor(Color[]) - Method in class com.imsl.chart.Dendrogram
Define colors for individual clusters.
setLineDashPattern(double[]) - Method in class com.imsl.chart.ChartNode
Sets the value of the "LineDashPattern" attribute.
setLineWidth(double) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "LineWidth" attribute.
setLocale(Locale) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "Locale" attribute.
setLocation(double, double) - Method in class com.imsl.chart.Annotation
Update the location of this Annotation instance.
setLow(double[]) - Method in class com.imsl.chart.ErrorBar
Convenience routine to set the "Low" attribute.
setLow(double[]) - Method in class com.imsl.chart.HighLowClose
Convenience routine to set the "Low" attribute.
setLowerBound(double[]) - Method in class com.imsl.math.DenseLP
Sets the lower bound, x_l, on the variables.
setLowerEndpointColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel
Sets the column number in x that contains the lower endpoint of the observation interval for full interval and right interval observations.
setMA(double[]) - Method in class com.imsl.stat.ARMAMaxLikelihood
Sets the initial values for the moving average terms to the q values in ma.
setMALags(int[]) - Method in class com.imsl.stat.ARMA
Sets the order of the moving average parameters.
setMarkerColor(Color) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "MarkerColor" attribute.
setMarkerColor(String) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "MarkerColor" attribute to a color specified by name.
setMarkerDashPattern(double[]) - Method in class com.imsl.chart.ChartNode
Sets the value of the "MarkerDashPattern" attribute.
setMarkerPulsingCycle(double) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "MarkerPulsingCycle" attribute.
setMarkerPulsingCycleOffset(double) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "MarkerPulsingCycleOffset" attribute.
setMarkerPulsingMaximumScale(double) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "MarkerPulsingMaximumScale" attribute.
setMarkerPulsingMinimumScale(double) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "MarkerPulsingMinimumScale" attribute.
setMarkerRotatingAxis(double, double, double) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "MarkerRotatingAxis" attribute.
setMarkerRotatingCycle(double) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "MarkerRotatingCycle" attribute.
setMarkerRotatingCycleOffset(double) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "MarkerRotatingCycleOffset" attribute.
setMarkerSize(double) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "MarkerSize" attribute.
setMarkerThickness(double) - Method in class com.imsl.chart.ChartNode
Sets the value of the "MarkerThickness" attribute.
setMarkerType(int) - Method in class com.imsl.chart.ChartNode
Sets the value of the "MarkerType" attribute.
setMarkerType(int) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "MarkerType" attribute.
setMaterial(Material) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "Material" attribute.
setMatrixType(int) - Method in class com.imsl.math.PrintMatrix
Set matrix type.
setMaxClass(int) - Method in class com.imsl.stat.ProportionalHazards
Sets an upper bound on the sum of the number of distinct values found among the classification variables in x.
setMaxEvaluations(int) - Method in class com.imsl.math.ZerosFunction
Sets the maximum number of function evaluations allowed.
setMaximumARLag(int) - Method in class com.imsl.stat.AutoARIMA
Defines the maximum AR lag used in the determination of the optimum (s,d) combination of method compute(int[] arOrders, int[] maOrders).
setMaximumBDFOrder(int) - Method in class com.imsl.math.FeynmanKac
Sets the maximum order of the BDF formulas.
setMaximumBestFound(int) - Method in class com.imsl.stat.SelectionRegression
Sets the maximum number of best regressions to be found.
setMaximumFunctionEvals(int) - Method in class com.imsl.math.BoundedLeastSquares
Sets the maximum number of function evaluations.
setMaximumFunctionEvaluations(int) - Method in class com.imsl.math.OdeAdamsGear
Sets the maximum number of function evaluations of y' allowed.
setMaximumGoodSaved(int) - Method in class com.imsl.stat.SelectionRegression
Sets the maximum number of good regressions for each subset size saved.
setMaximumIteration(int) - Method in class com.imsl.math.BoundedLeastSquares
Sets the maximum number of iterations.
setMaximumJacobianEvals(int) - Method in class com.imsl.math.BoundedLeastSquares
Sets the maximum number of Jacobian evaluations.
setMaximumStepsize(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Sets the maximum step size.
setMaximumStepsize(double) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Sets the maximum step size.
setMaximumStepSize(double) - Method in class com.imsl.math.BoundedLeastSquares
Sets the maximum allowable step size.
setMaximumStepsize(double) - Method in class com.imsl.math.FeynmanKac
Sets the maximum internal step size used by the integrator.
setMaximumStepsize(double) - Method in class com.imsl.math.MinUnconMultiVar
Set the maximum allowable stepsize to use.
setMaximumStepsize(double) - Method in class com.imsl.math.NonlinLeastSquares
Set the maximum allowable stepsize to use.
setMaximumStepsize(double) - Method in class com.imsl.math.ODE
Sets the maximum internal step size.
setMaximumStepsize(double) - Method in class com.imsl.math.OdeAdamsGear
Sets the maximum internal step size.
setMaximumStepsize(double) - Method in class com.imsl.math.OdeRungeKutta
Sets the maximum internal step size.
setMaximumSubsetSize(int) - Method in class com.imsl.stat.SelectionRegression
Sets the maximum subset size if R^2 criterion is used.
setMaximumTime(long) - Method in class com.imsl.math.MinConNLP
Sets the maximum time allowed for the solve step.
setMaximumTime(long) - Method in class com.imsl.math.NonNegativeLeastSquares
Sets the maximum time allowed for the solve step.
setMaximumTrainingIterations(int) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Sets the maximum number of iterations used by the nonlinear least squares solver.
setMaximumTrainingIterations(int) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Sets the maximum number of iterations to use in a training.
setMaximumValue(double) - Method in class com.imsl.chart.qc.ControlLimit
Set the maximum value of this control limit line.
setMaxIterations(int) - Method in class com.imsl.math.BoundedVariableLeastSquares
Sets the maximum number of iterations.
setMaxIterations(int) - Method in class com.imsl.math.ConjugateGradient
Sets the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.math.Eigen
Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.math.GenMinRes
Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.math.MinConNLP
Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.math.MinUnconMultiVar
Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.math.NonlinLeastSquares
Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.math.NonNegativeLeastSquares
Sets the maximum number of iterations.
setMaxIterations(int) - Method in class com.imsl.math.ZeroPolynomial
Sets the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.math.ZeroSystem
Sets the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.stat.ARAutoUnivariate
Sets the maximum number of iterations used for estimating the autoregressive coefficients.
setMaxIterations(int) - Method in class com.imsl.stat.ARMA
Sets the maximum number of iterations.
setMaxIterations(int) - Method in class com.imsl.stat.ARMAEstimateMissing
Sets the maximum number of estimation iterations for missing value estimation methods AR_1 and AR_P.
setMaxIterations(int) - Method in class com.imsl.stat.ARMAMaxLikelihood
Sets the maximum number of iterations.
setMaxIterations(int) - Method in class com.imsl.stat.CategoricalGenLinModel
Set the maximum number of iterations allowed.
setMaxIterations(int) - Method in class com.imsl.stat.ClusterKMeans
Sets the maximum number of iterations.
setMaxIterations(int) - Method in class com.imsl.stat.FactorAnalysis
Sets the maximum number of iterations in the iterative procedure.
setMaxIterations(int) - Method in class com.imsl.stat.NonlinearRegression
Sets the maximum number of iterations allowed during optimization
setMaxIterations(int) - Method in class com.imsl.stat.ProportionalHazards
Set the maximum number of iterations allowed.
setMaxKrylovDim(int) - Method in class com.imsl.math.GenMinRes
Set the maximum Krylov subspace dimension, i.e., the maximum allowable number of GMRES iterations allowed before restarting.
setMaxlag(int) - Method in class com.imsl.stat.ARMAEstimateMissing
Sets the maximum number of autoregressive lags when method AR_P is selected as the missing value estimation method.
setMaxOrder(int) - Method in class com.imsl.math.OdeAdamsGear
Sets the highest order formula to use of implicit METHOD_ADAMS type or METHOD_BDF type.
setMaxSigma(double) - Method in class com.imsl.stat.GARCH
Sets the value of the upperbound on the first element (sigma) of the array of returned estimated coefficients.
setMaxStep(int) - Method in class com.imsl.stat.FactorAnalysis
Sets the maximum number of step halvings allowed during an iteration.
setMaxSteps(int) - Method in class com.imsl.math.FeynmanKac
Sets the maximum number of internal steps allowed.
setMaxSteps(int) - Method in class com.imsl.math.ODE
Sets the maximum number of internal steps allowed.
setMaxStepsize(double) - Method in class com.imsl.stat.NonlinearRegression
Sets the maximum allowable stepsize.
setMaxSubintervals(int) - Method in class com.imsl.math.Quadrature
Sets the maximum number of subintervals allowed.
setMean(double) - Method in class com.imsl.stat.ARAutoUnivariate
Sets the estimate of the mean used for centering the time series z .
setMean(double) - Method in class com.imsl.stat.ARMA
Sets an initial estimate of the mean of the time series z.
setMean(double) - Method in class com.imsl.stat.ARMAEstimateMissing
Sets the mean value used to center the series.
setMean(double) - Method in class com.imsl.stat.ARMAMaxLikelihood
Sets the mean used for centering the series.
setMean(double) - Method in class com.imsl.stat.AutoCorrelation
Estimate mean of the time series x.
setMeans(double[]) - Method in class com.imsl.stat.StepwiseRegression
Sets the means of the variables.
setMeanX(double) - Method in class com.imsl.stat.CrossCorrelation
Estimate of the mean of time series x.
setMeanX(double[]) - Method in class com.imsl.stat.MultiCrossCorrelation
Estimate of the mean of each channel of x.
setMeanY(double) - Method in class com.imsl.stat.CrossCorrelation
Estimate of the mean of time series y.
setMeanY(double[]) - Method in class com.imsl.stat.MultiCrossCorrelation
Estimate of the mean of each channel of y.
setMethod(int) - Method in class com.imsl.math.GenMinRes
Set the implementation method to be used.
setMethod(int) - Method in class com.imsl.stat.ARMA
Sets the estimation method used for estimating the ARMA parameters.
setMethod(int) - Method in class com.imsl.stat.ClusterHierarchical
Sets the clustering method to be used.
setMethod(int) - Method in class com.imsl.stat.StepwiseRegression
Specifies the stepwise selection method, forward, backward, or stepwise Regression.
setMinimumSeparation(double) - Method in class com.imsl.math.ZerosFunction
Sets the minimum separation between accepted roots.
setMinimumStepsize(double) - Method in class com.imsl.math.ODE
Sets the minimum internal step size.
setMinimumValue(double) - Method in class com.imsl.chart.qc.ControlLimit
Set the minimum value of this control limit line.
setMissingValueMethod(int) - Method in class com.imsl.stat.ARMAEstimateMissing
Sets the current missing value estimation method to MEDIAN, CUBIC_SPLINE, AR_1, or AR_P.
setMissingValueMethod(int) - Method in class com.imsl.stat.Covariances
Sets the method used to exclude missing values in x from the computations, where Double.NaN is interpreted as the missing value code.
setModelIntercept(int) - Method in class com.imsl.stat.CategoricalGenLinModel
Sets the intercept option.
setModelOrder(int) - Method in class com.imsl.stat.ANOVAFactorial
Sets the number of factors to be included in the highest-way interaction in the model.
setModelOrder(int) - Method in class com.imsl.stat.RegressorsForGLM
Sets the order of the model.
setModelSelectionCriterion(int) - Method in class com.imsl.stat.AutoARIMA
Sets the model selection criterion.
setMRBar(double) - Method in class com.imsl.chart.qc.XmR
Sets the expected mean of all of the moving ranges of two observations.
setMullerTolerance(double) - Method in class com.imsl.math.ZerosFunction
Sets the tolerance used during refinement to determine if Müllers method is started.
setMultiplier(int) - Method in class com.imsl.stat.Random
Sets the multiplier for a linear congruential random number generator.
setMultiplierError(double) - Method in class com.imsl.math.MinConNLP
Set the error allowed in the multipliers.
setName(String) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "Name" attribute.
setNameBounds(String) - Method in class com.imsl.io.MPSReader
Sets the name of the BOUNDS set to be used.
setNameObjective(String) - Method in class com.imsl.io.MPSReader
Sets the name of the free row containing the objective.
setNameRanges(String) - Method in class com.imsl.io.MPSReader
Sets the name of the RANGES set to be used.
setNameRHS(String) - Method in class com.imsl.io.MPSReader
Sets the name of the RHS set to be used.
setNoColumnLabels() - Method in class com.imsl.math.PrintMatrixFormat
Turns off column labels.
setNode(ChartNode) - Method in class com.imsl.chart.Draw
Set the current ChartNode.
setNode(ChartNode) - Method in class com.imsl.chart.DrawMap
Set the current ChartNode.
setNode(ChartNode) - Method in class com.imsl.chart.DrawPick
Set the current ChartNode.
setNode(ChartNode) - Method in class com.imsl.chart.PickEvent
Sets the ChartNode.
setNorm(int) - Method in class com.imsl.math.ODE
Sets the switch for determining the error norm.
setNormTolerance(double) - Method in class com.imsl.math.NonNegativeLeastSquares
Sets the residual norm tolerance.
setNoRowLabels() - Method in class com.imsl.math.PrintMatrixFormat
Turns off row labels.
setNotch(boolean) - Method in class com.imsl.chart.BoxPlot
Sets the attribute "Notch".
setNumber(int) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "Number" attribute.
setNumberFormat(NumberFormat) - Method in class com.imsl.math.PrintMatrixFormat
Sets the NumberFormat to be used in formatting double and Complex entries.
setNumberGridPointsX(int) - Method in class com.imsl.chart3d.Surface
Sets the value of the "NumberGridPointsX" attribute.
setNumberGridPointsY(int) - Method in class com.imsl.chart3d.Surface
Sets the value of the "NumberGridPointsY" attribute.
setNumberOfEpochs(int) - Method in class com.imsl.datamining.neural.EpochTrainer
Sets the number of epochs.
setNumberOfRoots(int) - Method in class com.imsl.math.ZerosFunction
Sets the number of roots to be found.
setNumberOfThreads(int) - Method in class com.imsl.datamining.neural.EpochTrainer
Sets the number of processors to use during stage I training.
setNumericFactor(ComplexSparseCholesky.NumericFactor) - Method in class com.imsl.math.ComplexSparseCholesky
Sets the numeric Cholesky factor to use in solving a sparse complex Hermitian positive definite system of linear equations Ax=b.
setNumericFactor(SparseCholesky.NumericFactor) - Method in class com.imsl.math.SparseCholesky
Sets the numeric Cholesky factor to use in solving of a sparse positive definite system of linear equations Ax=b.
setNumericFactorizationMethod(int) - Method in class com.imsl.math.ComplexSparseCholesky
Defines the method used in the numerical factorization of the permuted input matrix.
setNumericFactorizationMethod(int) - Method in class com.imsl.math.SparseCholesky
Defines the method used in the numerical factorization of the permuted input matrix.
setObservationMax(int) - Method in class com.imsl.stat.CategoricalGenLinModel
Sets the maximum number of observations that can be handled in the linear programming.
setOffset(double) - Method in class com.imsl.chart.Text
Sets the offset.
setOpen(double[]) - Method in class com.imsl.chart.HighLowClose
Sets the attribute "Open".
setOptionalDistributionParameterColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel
Sets the column number in x that contains an optional distribution parameter for each observation.
setOrbit(boolean) - Method in class com.imsl.chart3d.Chart3D
Sets the value of the "Orbit" attribute.
setOrder(int[]) - Method in class com.imsl.chart.Dendrogram
Convenience routine to set the "Order" attribute.
setOrders(int[]) - Method in class com.imsl.stat.Difference
Sets the orders for the Difference object
setOrientation(int) - Method in class com.imsl.chart.Treemap
Sets the value of the "Orientation" attribute.
setOut(PrintStream) - Static method in class com.imsl.Warning
Reassigns the output stream.
setOut(PrintStream) - Method in class com.imsl.WarningObject
Reassigns the output stream.
setPageWidth(int) - Method in class com.imsl.math.PrintMatrix
Sets the page width.
setPaint(boolean) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "Paint" attribute.
setParallelMode(ArrayList[]) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Sets the trainer to be used in multi-threaded EpochTainer.
setParallelMode(ArrayList[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Sets the trainer to be used in multi-threaded EpochTainer.
setPenaltyBound(double) - Method in class com.imsl.math.MinConNLP
Set the universal bound for describing how much the unscaled penalty-term may deviate from zero.
setPercentage(double) - Method in class com.imsl.stat.SignTest
Sets the percentage percentile of the population.
setPercentageFactor(double[]) - Method in class com.imsl.math.NumericalDerivatives
Sets the percentage factor for differencing
setPercentages(double[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Set the untransformed cumulative percentages used during encoding and decoding.
setPercentile(double) - Method in class com.imsl.stat.SignTest
Sets the hypothesized percentile of the population.
setPerformanceTuningParameters(int, int) - Method in class com.imsl.math.ComplexSuperLU
Sets performance tuning parameters.
setPerformanceTuningParameters(int, int) - Method in class com.imsl.math.SuperLU
Sets performance tuning parameters.
setPeriods(int[]) - Method in class com.imsl.stat.AutoARIMA
Defines the periods used in the determination of the optimum model.
setPivotGrowth(boolean) - Method in class com.imsl.math.ComplexSuperLU
Specifies whether to compute the reciprocal pivot growth factor.
setPivotGrowth(boolean) - Method in class com.imsl.math.SuperLU
Specifies whether to compute the reciprocal pivot growth factor.
setPixels(int, int, int, int, ColorModel, byte[], int, int) - Method in class com.imsl.chart.WebSafeImageFilter
 
setPixels(int, int, int, int, ColorModel, int[], int, int) - Method in class com.imsl.chart.WebSafeImageFilter
 
setPopulationSize(int) - Method in class com.imsl.stat.LifeTables
Sets the population size at the beginning of the first age interval in requesting a population table.
setPosition(int, int) - Method in class com.imsl.chart3d.ColormapLegend
Sets the position of the legend.
setPosition(double, double, double) - Method in class com.imsl.chart3d.PointLight
Sets the value of the "Point" attribute to a light point.
setPosition(Point3f) - Method in class com.imsl.chart3d.PointLight
Sets the value of the "Point" attribute to a light point.
setPrior(int) - Method in class com.imsl.stat.DiscriminantAnalysis
Specifies the prior probabilities to be calculated as either equal or proportional priors.
setPrior(double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Specifies user supplied prior probabilities.
setProportionalWidth(boolean) - Method in class com.imsl.chart.BoxPlot
Sets the value of the attribute "ProportionalWidth".
setPValueIn(double) - Method in class com.imsl.stat.StepwiseRegression
Defines the largest p-value for variables entering the model.
setPValueOut(double) - Method in class com.imsl.stat.StepwiseRegression
Defines the smallest p-value for removing variables.
setQ(double[][]) - Method in class com.imsl.stat.KalmanFilter
Sets the Q matrix.
setRadialFunction(RadialBasis.Function) - Method in class com.imsl.math.RadialBasis
Sets the radial function.
setRandom(Random) - Method in class com.imsl.datamining.neural.EpochTrainer
Sets the random number generator used to perturb the initial stage 1 guesses.
setRandom(Random) - Method in class com.imsl.stat.Ranks
Sets the Random object.
setRandomSamples(Random, Random) - Method in class com.imsl.datamining.neural.EpochTrainer
Sets the random number generators used to select random training patterns in stage 1.
setRandomWeights(double[][], Random) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Initializes network weights using random weights.
setRange(double, double) - Method in class com.imsl.stat.ChiSquaredTest
Sets endpoints of the range of the distribution.
setRankTolerance(double) - Method in class com.imsl.math.NonNegativeLeastSquares
Sets the tolerance used for the incoming column rank deficient check.
setRbar(double) - Method in class com.imsl.chart.qc.XbarR
Sets the value of the "Rbar" attribute, the mean of the ranges for a series of samples.
setReference(double) - Method in class com.imsl.chart.ChartNode
Sets the value of the "Reference" attribute.
setRefinementType(int) - Method in class com.imsl.math.DenseLP
Set the type of refinement used.
setRelativeError(double) - Method in class com.imsl.math.ConjugateGradient
Sets the relative error used for stopping the algorithm.
setRelativeError(double) - Method in class com.imsl.math.GenMinRes
Set the stopping tolerance.
setRelativeError(double) - Method in class com.imsl.math.HyperRectangleQuadrature
Sets the relative error tolerance.
setRelativeError(double) - Method in class com.imsl.math.Quadrature
Sets the relative error tolerance.
setRelativeError(double) - Method in class com.imsl.math.ZeroSystem
Sets the relative error tolerance.
setRelativeError(double) - Method in class com.imsl.stat.ARMA
Sets the stopping criterion for use in the nonlinear equation solver.
setRelativeError(double) - Method in class com.imsl.stat.ARMAEstimateMissing
Sets the relative error used for the METHOD_OF_MOMENTS and LEAST_SQUARES estimation methods.
setRelativeError(double) - Method in class com.imsl.stat.ARMAOutlierIdentification
Sets the stopping criterion for use in the nonlinear equation solver.
setRelativeError(double) - Method in class com.imsl.stat.AutoARIMA
Sets the stopping criterion for use in the nonlinear equation solver.
setRelativeErrorTolerances(double[]) - Method in class com.imsl.math.FeynmanKac
Sets the relative error tolerances.
setRelativeErrorTolerances(double) - Method in class com.imsl.math.FeynmanKac
Sets the relative error tolerances.
setRelativeFcnTol(double) - Method in class com.imsl.math.BoundedLeastSquares
Sets the relative function tolerance.
setRelativeH(double) - Method in class com.imsl.chart.qc.CuSumStatus
Sets the value for relative h.
setRelativeTolerance(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Sets the relative tolerance.
setRelativeTolerance(double) - Method in class com.imsl.math.NonlinLeastSquares
Set the relative function tolerance.
setRelativeTolerance(double) - Method in class com.imsl.stat.NonlinearRegression
Sets the relative function tolerance
setResidualUpdating(int) - Method in class com.imsl.math.GenMinRes
Set the residual updating method to be used.
setResponseColumn(int) - Method in class com.imsl.stat.KaplanMeierEstimates
Sets the column index of x containing the response time for each observation.
setResponseColumn(int) - Method in class com.imsl.stat.ProportionalHazards
Sets the column index of x containing the response variable.
setRightEndTangent(double) - Method in class com.imsl.math.CsTCB
Sets the value of the tangent at the right endpoint.
setRightSons(int[]) - Method in class com.imsl.chart.Dendrogram
Convenience routine to set the "RightSons" attribute.
setRow(boolean) - Method in class com.imsl.stat.Dissimilarities
Identifies whether distances are computed between rows or columns of x.
setRule(int) - Method in class com.imsl.math.Quadrature
Set the Gauss-Kronrod rule.
setSampleSize(int) - Method in class com.imsl.chart.qc.ShewhartControlChart
Sets the value of the attribute "SampleSize".
setSampleSize(int[]) - Method in class com.imsl.chart.qc.ShewhartControlChart
Sets the value of the attribute "SampleSize".
setScale(double) - Method in class com.imsl.math.ODE
Sets the scaling factor.
setScale(double[]) - Method in class com.imsl.stat.NonlinearRegression
Sets the scaling array for theta.
setScaledStepTol(double) - Method in class com.imsl.math.BoundedLeastSquares
Sets the scaled step tolerance.
setScaleFont(double) - Method in class com.imsl.chart.Draw
Set a factor by which fonts are to be scaled.
setScalingBound(double) - Method in class com.imsl.math.MinConNLP
Set the scaling bound for the internal automatic scaling of the objective function.
setScalingFactors(double[]) - Method in class com.imsl.math.NumericalDerivatives
Sets the scaling factors for the y values.
setScalingOption(int) - Method in class com.imsl.stat.Dissimilarities
Sets the scaling option used if the L2_NORM, L1_NORM, or INFINITY_NORM distance methods are specified.
setScalingVector(double[]) - Method in class com.imsl.math.BoundedLeastSquares
Sets the scaling vector for the variables.
setScreenSize(Dimension) - Method in class com.imsl.chart.ChartNode
Sets the value of the "ScreenSize" attribute.
setSeed(long) - Method in class com.imsl.stat.Random
Sets the seed.
setSigma(double) - Method in class com.imsl.chart.qc.CuSumStatus
Sets the standard deviation of the data.
setSize(Dimension) - Method in class com.imsl.chart.ChartNode
Sets the value of the "Size" attribute.
setSize(Dimension) - Method in class com.imsl.chart.JspBean
Sets the size of the generated image.
setSize(int, int) - Method in class com.imsl.chart.JspBean
Sets the size of the generated image.
setSkipWeekends(boolean) - Method in class com.imsl.chart.ChartNode
Sets the value of the "SkipWeekends" attribute.
setSolveMethod(int) - Method in class com.imsl.math.OdeAdamsGear
Indicates which method to use for solving the formula equations.
setSorted(boolean) - Method in class com.imsl.stat.KaplanMeierEstimates
Sets the boolean to indicate that the column of response times in x are already sorted.
setSpread(double) - Method in class com.imsl.datamining.neural.ScaleFilter
Set the measure of spread to be used during z-score scaling.
setStep(double) - Method in class com.imsl.math.MinUncon
Set the stepsize to use when changing x.
setStepControlMethod(int) - Method in class com.imsl.math.FeynmanKac
Sets the step control method used in the integration of the Feynman-Kac PDE.
setStepTolerance(double) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Set the step tolerance used to step between weights.
setStepTolerance(double) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Sets the scaled step tolerance.
setStepTolerance(double) - Method in class com.imsl.math.MinUnconMultiVar
Set the scaled step tolerance to use when changing x.
setStepTolerance(double) - Method in class com.imsl.math.NonlinLeastSquares
Set the scaled step tolerance.
setStepTolerance(double) - Method in class com.imsl.stat.NonlinearRegression
Sets the step tolerance used to step between two points.
setStratumColumn(int) - Method in class com.imsl.stat.KaplanMeierEstimates
Sets the column index of x containing the stratum number for each observation.
setStratumColumn(int) - Method in class com.imsl.stat.ProportionalHazards
Sets the column index of x containing the stratification variable.
setStratumRatio(double) - Method in class com.imsl.stat.ProportionalHazards
Set the ratio at which a stratum is split into two strata.
setString(String) - Method in class com.imsl.chart.Annotation
Sets the String for the Text object to render.
setString(String) - Method in class com.imsl.chart.Text
Sets the string for this Text object.
setSurfaceType(int) - Method in class com.imsl.chart3d.Surface
Sets the attribute "SurfaceType".
setSymbolicFactor(ComplexSparseCholesky.SymbolicFactor) - Method in class com.imsl.math.ComplexSparseCholesky
Sets the symbolic Cholesky factor to use in solving a sparse complex Hermitian positive definite system of linear equations Ax=b.
setSymbolicFactor(SparseCholesky.SymbolicFactor) - Method in class com.imsl.math.SparseCholesky
Sets the symbolic Cholesky factor to use in solving a sparse positive definite system of linear equations Ax=b.
setSymmetricMode(boolean) - Method in class com.imsl.math.ComplexSuperLU
Specifies whether to use the symmetric mode.
setSymmetricMode(boolean) - Method in class com.imsl.math.SuperLU
Specifies whether to use the symmetric mode.
setTension(double[]) - Method in class com.imsl.math.CsTCB
Sets the tension values at the data points.
setText(Text) - Method in class com.imsl.chart.Annotation
Sets the Text object to render.
setTextAngle(int) - Method in class com.imsl.chart.ChartNode
Sets the value of the "TextAngle" attribute.
setTextColor(Color) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "TextColor" attribute.
setTextColor(String) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "TextColor" attribute to a color specified by name.
setTextColor(Color) - Method in class com.imsl.chart.ChartNode
Sets the value of the "TextColor" attribute.
setTextColor(String) - Method in class com.imsl.chart.ChartNode
Sets the value of the "TextColor" attribute to a color specified by name.
setTextFormat(Format) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "TextFormat" attribute.
setTextFormat(String) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "TextFormat" attribute.
setTickInterval(double) - Method in class com.imsl.chart.Axis1D
Sets the tick interval.
setTickInterval(double) - Method in class com.imsl.chart.AxisR
Sets the tick interval.
setTickInterval(double) - Method in class com.imsl.chart3d.Axis3D
Sets the tick interval.
setTickLength(double) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "TickLength" attribute.
setTicks(double[]) - Method in class com.imsl.chart.Axis1D
Sets the value of the "Ticks" attribute.
setTicks(double[]) - Method in class com.imsl.chart3d.Axis3D
Sets the value of the "Ticks" attribute.
setTicks(double[]) - Method in class com.imsl.chart3d.ColormapLegend
Sets the value of the "Ticks" attribute.
setTieBreaker(int) - Method in class com.imsl.stat.Ranks
Sets the tie breaker for Ranks.
setTiesOption(int) - Method in class com.imsl.stat.ProportionalHazards
Sets the method for handling ties.
setTimeBarrier(double) - Method in class com.imsl.math.FeynmanKac
Sets a barrier for the integration in the time direction.
setTimeDependence(boolean[]) - Method in class com.imsl.math.FeynmanKac
Sets the time dependence of the coefficients, boundary conditions and function phi in the Feynman Kac equation.
setTitle(String) - Method in class com.imsl.chart.ChartNode
Sets the value of the "Title" attribute.
setTitle(Text) - Method in class com.imsl.chart.ChartNode
Sets the value of the "Title" attribute.
setTitle(String) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "Title" attribute.
setTitle(String) - Method in class com.imsl.math.PrintMatrix
Sets matrix title
setTolerance(int) - Method in class com.imsl.chart.DrawMap
Set the minimum distance that an event can be from a point or a line and still be considered a hit.
setTolerance(int) - Method in class com.imsl.chart.DrawPick
Set the minimum distance that an event can be from a point or a line and still be considered a hit.
setTolerance(double) - Method in class com.imsl.math.BoundedVariableLeastSquares
Sets the internal tolerance used to determine the relative linear dependence of a column vector for a variable moved from its initial value.
setTolerance(double) - Method in class com.imsl.math.MinConGenLin
Sets the nonnegative tolerance on the first order conditions at the calculated solution.
setTolerance(double) - Method in class com.imsl.math.MinConNLP
Set the desired precision of the solution.
setTolerance(double) - Method in class com.imsl.math.ODE
Sets the error tolerance.
setTolerance(double) - Method in class com.imsl.stat.ARMAMaxLikelihood
Sets the tolerance for the convergence algorithm.
setTolerance(double) - Method in class com.imsl.stat.CategoricalGenLinModel
Initializes the tolerance used in determining linear dependence.
setTolerance(double) - Method in class com.imsl.stat.InverseCdf
Sets the tolerance to be used as the convergence criterion.
setTolerance(double) - Method in class com.imsl.stat.KalmanFilter
Sets the tolerance used in determining linear dependence.
setTolerance(double) - Method in class com.imsl.stat.StepwiseRegression
The tolerance used to detect linear dependence among the independent variables.
setToolTip(String) - Method in class com.imsl.chart.ChartNode
Sets the value of the "ToolTip" attribute.
setTransform(int) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "Transform" attribute.
setTransformType(int) - Method in class com.imsl.stat.ClusterHierarchical
Sets the type of transformation.
setTransitionMatrix(double[][]) - Method in class com.imsl.stat.KalmanFilter
Sets the transition matrix.
setTrustRegion(double) - Method in class com.imsl.math.BoundedLeastSquares
Sets the size of initial trust region radius.
setTTestNull(double) - Method in class com.imsl.stat.NormOneSample
Sets the Null hypothesis value for t test for the mean.
setTTestNull(double) - Method in class com.imsl.stat.NormTwoSample
Sets the Null hypothesis value for t-test for the mean.
setType(int) - Method in class com.imsl.chart.Axis1D
Sets the type of this node.
setUnequalVariances(boolean) - Method in class com.imsl.stat.NormTwoSample
Specifies whether to return statistics based on equal or unequal variances.
setupMapping() - Method in class com.imsl.chart.Axis
Initializes the mappings between user and coordinate space.
setupMapping() - Method in class com.imsl.chart.AxisXY
Initializes the mappings between user and coordinate space.
setupMapping() - Method in class com.imsl.chart.Pie
Initializes the mappings between user and coordinate space.
setupMapping() - Method in class com.imsl.chart.Polar
Initializes the mappings between user and coordinate space.
setupMapping(Axis1D) - Method in interface com.imsl.chart.Transform
Initializes the mappings between user and coordinate space.
setupMapping(Axis1D) - Method in class com.imsl.chart.TransformDate
Initializes the mappings between user and coordinate space.
setUpperBound(double[]) - Method in class com.imsl.math.DenseLP
Sets the upper bound, x_u, on the variables.
setUpperBound(int) - Method in class com.imsl.stat.CategoricalGenLinModel
Sets the upper bound on the sum of the number of distinct values taken on by each classification variable.
setUpperEndpointColumn(int) - Method in class com.imsl.stat.CategoricalGenLinModel
Sets the column number in x that contains the upper endpoint of the observation interval for full interval and left interval observations.
setUpperLimit(double[]) - Method in class com.imsl.math.DenseLP
Sets the upper limit of the constraints.
setUseBackPropagation(boolean) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Sets whether or not to use the back propagation algorithm for gradient calculations during network training.
setValue(double) - Method in class com.imsl.chart.qc.ControlLimit
Sets the value of this control limit line.
setValue(double[]) - Method in class com.imsl.chart.qc.ControlLimit
Sets the value of this control limit line to an array of values.
setValue(double) - Method in class com.imsl.datamining.neural.InputNode
Sets the value of this Node.
setVarianceEstimationMethod(int) - Method in class com.imsl.stat.FactorAnalysis
Sets the variance estimation method.
setVariances(double[]) - Method in class com.imsl.stat.FactorAnalysis
Sets the variances.
setVectorProducts(GenMinRes.VectorProducts) - Method in class com.imsl.math.GenMinRes
Sets the user-supplied functions for the inner product and, optionally, the norm to be used in the Gram-Schmidt implementations.
setViewPlatformTransformation(Transform3D) - Method in class com.imsl.chart3d.Chart3D
Sets the transformation for the view platform.
setViewport(double[]) - Method in class com.imsl.chart.ChartNode
Sets the value of the "Viewport" attribute.
setViewport(double, double, double, double) - Method in class com.imsl.chart.ChartNode
Sets the value of the "Viewport" attribute.
setViewport(double[]) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "Viewport" attribute.
setViewport(double, double, double, double, double, double) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "Viewport" attribute.
setViolationBound(double) - Method in class com.imsl.math.MinConNLP
Set the scalar which defines allowable constraint violations of the final accepted result.
setVisibleFaces(int) - Method in class com.imsl.chart3d.AxisBox
Sets the "VisibleFaces" attribute indicating which faces of the box are to be drawn.
setWarning(SQLWarning) - Method in class com.imsl.io.AbstractFlatFile
Sets a SQLWarning.
setWarning(WarningObject) - Static method in class com.imsl.Warning
Sets a new WarningObject.
setWbar(double) - Method in class com.imsl.chart.qc.XbarS
Sets the value of the "Wbar" attribute, the within sample variation for a series of samples.
setWeight(double) - Method in class com.imsl.datamining.neural.Link
Sets the weight for this Link.
setWeights(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Sets the weights for the Links in this Network.
setWeights(double[]) - Method in class com.imsl.datamining.neural.Network
Sets the weights.
setWeights(double[]) - Method in class com.imsl.stat.ClusterKMeans
Sets the weight for each observation.
setWeights(double[]) - Method in class com.imsl.stat.Covariances
Sets the weight for each observation.
setWindow(double, double) - Method in class com.imsl.chart.Axis1D
Sets the window for an Axis1D.
setWindow(double[]) - Method in class com.imsl.chart.Axis1D
Sets the window for an Axis1D.
setWindow(double) - Method in class com.imsl.chart.AxisR
Sets the Window attribute.
setWindow(double, double) - Method in class com.imsl.chart.AxisTheta
Sets the window for an AxisTheta.
setWindow(double[]) - Method in class com.imsl.chart.AxisTheta
Sets the window for an AxisTheta.
setWindow(double[]) - Method in class com.imsl.chart.AxisXY
Sets the window in user coordinates along an axis.
setWindow(double, double) - Method in class com.imsl.chart3d.Axis3D
Sets the window for an Axis1D.
setWindow(double[]) - Method in class com.imsl.chart3d.Axis3D
Sets the window for an Axis1D.
setWindow(double, double) - Method in class com.imsl.chart3d.ColormapLegend
Sets the window for a ColormapLegend.
setWindow(double[]) - Method in class com.imsl.chart3d.ColormapLegend
Sets the window for a ColormapLegend.
setX(Object) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "X" attribute.
setX(double[]) - Method in class com.imsl.chart.qc.CuSumStatus
Sets the x-coordinates of the bars.
setX(double[]) - Method in class com.imsl.chart.qc.ShewhartControlChart
Sets the x-coordinates of the data.
setXKnots(double[]) - Method in class com.imsl.math.Spline2DLeastSquares
Sets the knot sequences of the spline in the x-direction.
setXlowerBound(double[]) - Method in class com.imsl.math.MinConNLP
Set the lower bounds on the variables.
setXOrder(int) - Method in class com.imsl.math.Spline2DLeastSquares
Sets the order of the spline in the x-direction.
setXscale(double[]) - Method in class com.imsl.math.MinConNLP
Set the internal scaling of the variables.
setXscale(double[]) - Method in class com.imsl.math.MinUnconMultiVar
Set the diagonal scaling matrix for the variables.
setXscale(double[]) - Method in class com.imsl.math.NonlinLeastSquares
Set the diagonal scaling matrix for the variables.
setXScale(double) - Method in class com.imsl.math.ZerosFunction
Sets the the scaling in the x-coordinate.
setXupperBound(double[]) - Method in class com.imsl.math.MinConNLP
Set the upper bounds on the variables.
setXWeights(double[]) - Method in class com.imsl.math.Spline2DLeastSquares
Sets the weights for the least-squares fit in the x-direction.
setY(Object) - Method in class com.imsl.chart.AbstractChartNode
Sets the value of the "Y" attribute.
setYKnots(double[]) - Method in class com.imsl.math.Spline2DLeastSquares
Sets the knot sequences of the spline in the y-direction.
setYOrder(int) - Method in class com.imsl.math.Spline2DLeastSquares
Sets the order of the spline in the y-direction.
setYWeights(double[]) - Method in class com.imsl.math.Spline2DLeastSquares
Sets the weights for the least-squares fit in the y-direction.
setZ(Object) - Method in class com.imsl.chart3d.ChartNode3D
Sets the value of the "Z" attribute.
setZeroCorrection(double) - Method in class com.imsl.datamining.NaiveBayesClassifier
Specifies the replacement value to be used for conditional probabilities equal to zero.
setZRange(double[]) - Method in class com.imsl.chart.Treemap
Set the Z data (shading) range, range = {zmin,zmax}.
Sfun - Class in com.imsl.math
Collection of special functions.
ShapiroWilkWTest() - Method in class com.imsl.stat.NormalityTest
Performs the Shapiro-Wilk W test.
ShewhartControlChart - Class in com.imsl.chart.qc
ShewhartControlChart is the base class for the Shewhart control charts.
ShewhartControlChart(AxisXY) - Constructor for class com.imsl.chart.qc.ShewhartControlChart
Constructs a Shewhart control chart.
shortValue() - Method in class com.imsl.math.Complex
Returns the value of the real part as a short.
sigma(double, double) - Method in interface com.imsl.math.FeynmanKac.PdeCoefficients
Returns the value of the sigma coefficient at the given point.
sigmaPrime(double, double) - Method in interface com.imsl.math.FeynmanKac.PdeCoefficients
Returns the value of sigma^prime=frac{partial sigma(x,t)}{partial x} at the given point.
sign(double, double) - Static method in class com.imsl.math.Sfun
Returns the value of x with the sign of y.
SignTest - Class in com.imsl.stat
Performs a sign test.
SignTest(double[]) - Constructor for class com.imsl.stat.SignTest
Constructor for SignTest.
sin(Complex) - Static method in class com.imsl.math.Complex
Returns the sine of a Complex.
sin(double) - Static method in class com.imsl.math.JMath
Returns the sine of a double.
SingularMatrixException - Exception in com.imsl.math
The matrix is singular.
SingularMatrixException() - Constructor for exception com.imsl.math.SingularMatrixException
 
sinh(Complex) - Static method in class com.imsl.math.Complex
Returns the hyperbolic sine of a Complex.
sinh(double) - Static method in class com.imsl.math.Hyperbolic
Returns the hyperbolic sine of its argument.
skewness(double[]) - Static method in class com.imsl.stat.Summary
Returns the skewness of the given data set.
skewness(double[], double[]) - Static method in class com.imsl.stat.Summary
Returns the skewness of the given data set and associated weights.
SKIP - Static variable in class com.imsl.math.NumericalDerivatives
Indicates a variable to be skipped.
skip(int) - Method in class com.imsl.stat.Random
Resets the seed to skip ahead in the base linear congruential generator.
sln(double, double, int) - Static method in class com.imsl.finance.Finance
Returns the depreciation of an asset using the straight line method.
SOFTMAX - Static variable in interface com.imsl.datamining.neural.Activation
The softmax activation function.
solve() - Method in class com.imsl.math.BoundedLeastSquares
Solves a nonlinear least-squares problem subject to bounds on the variables using a modified Levenberg-Marquardt algorithm.
solve() - Method in class com.imsl.math.BoundedVariableLeastSquares
Find the solution x to the problem for the current constraints.
solve(double[]) - Method in class com.imsl.math.Cholesky
Solve Ax = b where A is a positive definite matrix with elements of type double.
solve(Complex[]) - Method in class com.imsl.math.ComplexLU
Return the solution x of the linear system Ax = b using the LU factorization of A.
solve(Complex[][], Complex[]) - Static method in class com.imsl.math.ComplexLU
Solve Ax = b for x using the LU factorization of A.
solve(Complex[]) - Method in class com.imsl.math.ComplexSparseCholesky
Computes the solution of a sparse Hermitian positive definite system of linear equations Ax=b.
solve(Complex[]) - Method in class com.imsl.math.ComplexSuperLU
Computation of the solution vector for the system Ax = b.
solve(double[]) - Method in class com.imsl.math.ConjugateGradient
Solves a real symmetric positive or negative definite system Ax=b using a conjugate gradient method with or without preconditioning.
solve() - Method in class com.imsl.math.DenseLP
Solves the problem using an active set method.
solve(double[][], boolean) - Method in class com.imsl.math.Eigen
Solves for the eigenvalues and (optionally) the eigenvectors of a real square matrix.
solve(double[]) - Method in class com.imsl.math.GenMinRes
Generate an approximate solution to Ax=b using the Generalized Residual Method.
solve(double[]) - Method in class com.imsl.math.LU
Return the solution x of the linear system Ax = b using the LU factorization of A.
solve(double[][], double[]) - Static method in class com.imsl.math.LU
Solve Ax = b for x using the LU factorization of A.
solve() - Method in class com.imsl.math.MinConGenLin
Minimizes a general objective function subject to linear equality/inequality constraints.
solve(MinConNLP.Function) - Method in class com.imsl.math.MinConNLP
Solve a general nonlinear programming problem using the successive quadratic programming algorithm with a finite-difference gradient or with a user-supplied gradient.
solve(NonlinLeastSquares.Function) - Method in class com.imsl.math.NonlinLeastSquares
Solve a nonlinear least-squares problem using a modified Levenberg-Marquardt algorithm and a Jacobian.
solve() - Method in class com.imsl.math.NonNegativeLeastSquares
Finds the solution to the problem for the current constraints.
solve(double, double, double[]) - Method in class com.imsl.math.OdeAdamsGear
Integrates the ODE system from t to tEnd.
solve(double, double, double[]) - Method in class com.imsl.math.OdeRungeKutta
Integrates the ODE system from t to tEnd.
solve(double[]) - Method in class com.imsl.math.QR
Returns the solution to the least-squares problem Ax = b.
solve(double[], double) - Method in class com.imsl.math.QR
Returns the solution to the least-squares problem Ax = b using an input tolerance.
solve(double[]) - Method in class com.imsl.math.SparseCholesky
Computes the solution of a sparse real symmetric positive definite system of linear equations Ax=b.
solve(double[]) - Method in class com.imsl.math.SuperLU
Computation of the solution vector for the system Ax = b.
solve(ZeroSystem.Function) - Method in class com.imsl.math.ZeroSystem
Solve a system of nonlinear equations using the modified Powell hybrid algorithm
solve() - Method in class com.imsl.stat.CategoricalGenLinModel
Returns the parameter estimates and associated statistics for a CategoricalGenLinModel object.
solve(NonlinearRegression.Function) - Method in class com.imsl.stat.NonlinearRegression
Solves the least squares problem and returns the regression coefficients.
SOLVE_CHORD_COMPUTED_DIAGONAL - Static variable in class com.imsl.math.OdeAdamsGear
A chord method and a diagonal matrix based on a directional directive
SOLVE_CHORD_COMPUTED_JACOBIAN - Static variable in class com.imsl.math.OdeAdamsGear
A chord or modified Newton method and a divided differences Jacobian
SOLVE_CHORD_USER_JACOBIAN - Static variable in class com.imsl.math.OdeAdamsGear
A chord or modified Newton method and a user-supplied Jacobian
SOLVE_FUNCTION_ITERATION - Static variable in class com.imsl.math.OdeAdamsGear
A function iteration or successive substitution method
solveConjugateTranspose(Complex[]) - Method in class com.imsl.math.ComplexSuperLU
Computation of the solution vector for the system A^Hx = b.
solveTranspose(Complex[]) - Method in class com.imsl.math.ComplexLU
Return the solution x of the linear system A^T x = b.
solveTranspose(Complex[]) - Method in class com.imsl.math.ComplexSuperLU
Computation of the solution vector for the system A^Tx = b.
solveTranspose(double[]) - Method in class com.imsl.math.LU
Return the solution x of the linear system A^T = b.
solveTranspose(double[]) - Method in class com.imsl.math.SuperLU
Computation of the solution vector for the system A^Tx = b.
Sort - Class in com.imsl.stat
A collection of sorting functions.
SORTED_AS_PER_OBSERVATIONS - Static variable in class com.imsl.stat.ProportionalHazards
Failures are assumed to occur in the same order as the observations input in x.
SparseCholesky - Class in com.imsl.math
Sparse Cholesky factorization of a matrix of type SparseMatrix.
SparseCholesky(SparseMatrix) - Constructor for class com.imsl.math.SparseCholesky
Constructs the matrix structure for the Cholesky factorization of a sparse symmetric positive definite matrix of type SparseMatrix.
SparseCholesky.NotSPDException - Exception in com.imsl.math
The matrix is not symmetric, positive definite.
SparseCholesky.NotSPDException() - Constructor for exception com.imsl.math.SparseCholesky.NotSPDException
 
SparseCholesky.NumericFactor - Class in com.imsl.math
The numeric Cholesky factorization of a matrix.
SparseCholesky.SymbolicFactor - Class in com.imsl.math
The symbolic Cholesky factorization of a matrix.
SparseMatrix - Class in com.imsl.math
Sparse matrix of type double.
SparseMatrix(int, int) - Constructor for class com.imsl.math.SparseMatrix
Creates a new instance of SparseMatrix.
SparseMatrix(SparseMatrix) - Constructor for class com.imsl.math.SparseMatrix
Creates a new instance of SparseMatrix which is a copy of another SparseMatrix.
SparseMatrix(SparseMatrix.SparseArray) - Constructor for class com.imsl.math.SparseMatrix
Constructs a sparse matrix from a SparseArray object.
SparseMatrix(int, int, int[][], double[][]) - Constructor for class com.imsl.math.SparseMatrix
Constructs a sparse matrix from SparseArray (Java Sparse Array) data.
SparseMatrix.SparseArray - Class in com.imsl.math
The SparseArray class uses public fields to hold the data for a sparse matrix in the Java Sparse Array format.
SparseMatrix.SparseArray() - Constructor for class com.imsl.math.SparseMatrix.SparseArray
 
SPECTRAL - Static variable in interface com.imsl.chart.Colormap
Spectral colormap.
Spline - Class in com.imsl.math
Spline represents and evaluates univariate piecewise polynomial splines.
Spline() - Constructor for class com.imsl.math.Spline
 
Spline2D - Class in com.imsl.math
Represents and evaluates tensor-product splines.
Spline2D() - Constructor for class com.imsl.math.Spline2D
 
Spline2DInterpolate - Class in com.imsl.math
Computes a two-dimensional, tensor-product spline interpolant from two-dimensional, tensor-product data.
Spline2DInterpolate(double[], double[], double[][]) - Constructor for class com.imsl.math.Spline2DInterpolate
Constructor for Spline2DInterpolate.
Spline2DInterpolate(double[], double[], double[][], int, int) - Constructor for class com.imsl.math.Spline2DInterpolate
Constructor for Spline2DInterpolate.
Spline2DInterpolate(double[], double[], double[][], int, int, double[], double[]) - Constructor for class com.imsl.math.Spline2DInterpolate
Constructor for Spline2DInterpolate.
Spline2DLeastSquares - Class in com.imsl.math
Computes a two-dimensional, tensor-product spline approximant using least squares.
Spline2DLeastSquares(double[], double[], double[][], int, int) - Constructor for class com.imsl.math.Spline2DLeastSquares
Constructor for Spline2DLeastSquares.
SplineData - Class in com.imsl.chart
A data set created from a Spline.
SplineData(ChartNode, Spline) - Constructor for class com.imsl.chart.SplineData
Creates a data node from Spline values.
sqrt(Complex) - Static method in class com.imsl.math.Complex
Returns the square root of a Complex, with a branch cut along the negative real axis.
sqrt(double) - Static method in class com.imsl.math.JMath
Returns the square root of a double.
SQUASH - Static variable in interface com.imsl.datamining.neural.Activation
The squash activation function, g(x) = frac{x}{1+|x|}
STANDARD_GAMMA - Static variable in interface com.imsl.chart.Colormap
Standard gamma colormap.
STANDARD_METHOD - Static variable in class com.imsl.math.ComplexSparseCholesky
Indicates that the method of George/Liu (1981) is used for numeric factorization.
STANDARD_METHOD - Static variable in class com.imsl.math.SparseCholesky
Indicates the method of George/Liu (1981) will be used for numeric factorization.
standardDeviation(double[]) - Static method in class com.imsl.stat.Summary
Returns the population standard deviation of the given data set.
standardDeviation(double[], double[]) - Static method in class com.imsl.stat.Summary
Returns the population standard deviation of the given data set and associated weights.
start(Chart) - Method in class com.imsl.chart.Draw
Called just before a chart is drawn.
startErrorBar() - Method in class com.imsl.chart.Draw
Start drawing an error bar.
startErrorBar() - Method in class com.imsl.chart.DrawMap
 
startErrorBar() - Method in class com.imsl.chart.DrawPick
Start ErrorBar
startFill() - Method in class com.imsl.chart.Draw
Start drawing a filled region.
startFill() - Method in class com.imsl.chart.DrawMap
 
startFill() - Method in class com.imsl.chart.DrawPick
Fill
startImage() - Method in class com.imsl.chart.Draw
Start drawing an image.
startImage() - Method in class com.imsl.chart.DrawMap
 
startImage() - Method in class com.imsl.chart.DrawPick
Start Image
startLine() - Method in class com.imsl.chart.Draw
Start drawing lines.
startLine() - Method in class com.imsl.chart.DrawMap
Start drawing lines.
startLine() - Method in class com.imsl.chart.DrawPick
Start drawing lines.
startMarker() - Method in class com.imsl.chart.Draw
Start drawing markers.
startMarker() - Method in class com.imsl.chart.DrawMap
Start drawing markers.
startMarker() - Method in class com.imsl.chart.DrawPick
Start drawing markers.
startText() - Method in class com.imsl.chart.Draw
Start drawing text.
startText() - Method in class com.imsl.chart.DrawMap
 
startText() - Method in class com.imsl.chart.DrawPick
Start drawing text
STD_DEV - Static variable in class com.imsl.stat.Dissimilarities
Indicates scaling by the standard deviation.
STDEV_CORRELATION_MATRIX - Static variable in class com.imsl.stat.Covariances
Indicates correlation matrix except for the diagonal elements which are the standard deviations
STEPWISE_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression
Indicates stepwise regression.
StepwiseRegression - Class in com.imsl.stat
Builds multiple linear regression models using forward selection, backward selection, or stepwise selection.
StepwiseRegression(double[][], double[]) - Constructor for class com.imsl.stat.StepwiseRegression
Creates a new instance of StepwiseRegression.
StepwiseRegression(double[][], double[], double[]) - Constructor for class com.imsl.stat.StepwiseRegression
Creates a new instance of weighted StepwiseRegression.
StepwiseRegression(double[][], double[], double[], double[]) - Constructor for class com.imsl.stat.StepwiseRegression
Creates a new instance of weighted StepwiseRegression using observation frequencies.
StepwiseRegression(double[][], int) - Constructor for class com.imsl.stat.StepwiseRegression
Creates a new instance of StepwiseRegression from a user-supplied variance-covariance matrix.
StepwiseRegression.CoefficientTTests - Class in com.imsl.stat
CoefficientTTests contains statistics related to the student-t test, for each regression coefficient.
StepwiseRegression.CyclingIsOccurringException - Exception in com.imsl.stat
Cycling is occurring.
StepwiseRegression.CyclingIsOccurringException(int) - Constructor for exception com.imsl.stat.StepwiseRegression.CyclingIsOccurringException
Constructs a CyclingIsOccurringException.
StepwiseRegression.NoVariablesEnteredException - Exception in com.imsl.stat
No Variables can enter the model.
StepwiseRegression.NoVariablesEnteredException() - Constructor for exception com.imsl.stat.StepwiseRegression.NoVariablesEnteredException
Constructs a NoVariablesEnteredException.
stop() - Method in class com.imsl.chart.Draw
Called when a chart is finished being drawn.
STRICT_LOWER_TRIANGULAR - Static variable in class com.imsl.math.PrintMatrix
This flag as the argument to setMatrixType, indicates that only the strict lower triangular elements of the matrix are to be printed.
STRICT_UPPER_TRIANGULAR - Static variable in class com.imsl.math.PrintMatrix
This flag as the argument to setMatrixType, indicates that only the strict upper triangular elements of the matrix are to be printed.
stringToObject(Class, String) - Method in class com.imsl.chart.xml.ChartXML
Converts a String into an Object of the given class.
studentsT(double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the Student's t cumulative probability distribution function.
studentsT(double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the Student's t cumulative probability distribution function.
subtract(Complex, Complex) - Static method in class com.imsl.math.Complex
Returns the difference of two Complex objects, x-y.
subtract(Complex, double) - Static method in class com.imsl.math.Complex
Returns the difference of a Complex object and a double, x-y.
subtract(double, Complex) - Static method in class com.imsl.math.Complex
Returns the difference of a double and a Complex object, x-y.
subtract(Complex[][], Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Subtract two Complex rectangular arrays, a - b.
subtract(double[][], double[][]) - Static method in class com.imsl.math.Matrix
Subtract two rectangular arrays, a - b.
subtract(Physical, Physical) - Static method in class com.imsl.math.Physical
Subtract two compatible Physical objects.
suffix - Static variable in class com.imsl.math.Complex
String used in converting Complex to String.
SUM_OF_SQUARES - Static variable in class com.imsl.datamining.neural.QuasiNewtonTrainer
Compute the sum of squares error.
SUM_TO_ZERO - Static variable in class com.imsl.stat.RegressorsForGLM
The n-1 dummies are defined in terms of the indicator variables so that for balanced data, the usual summation restrictions are imposed on the regression coefficients.
Summary - Class in com.imsl.stat
Computes basic univariate statistics.
Summary() - Constructor for class com.imsl.stat.Summary
Constructs a new summary statistics object.
SuperLU - Class in com.imsl.math
Computes the LU factorization of a general sparse matrix of type SparseMatrix by a column method and solves the real sparse linear system of equations Ax=b.
SuperLU(SparseMatrix) - Constructor for class com.imsl.math.SuperLU
Constructor for SuperLU.
Surface - Class in com.imsl.chart3d
Surface from a function or from a set of scattered data points.
Surface(AxisXYZ, Surface.ZFunction, double, double, double, double) - Constructor for class com.imsl.chart3d.Surface
Creates a surface from a function.
Surface(AxisXYZ, double[], double[], double[][]) - Constructor for class com.imsl.chart3d.Surface
Creates a surface from a gridded data set.
Surface(AxisXYZ, double[], double[], double[][], Color[][]) - Constructor for class com.imsl.chart3d.Surface
Creates a colored surface from a gridded data set.
Surface(AxisXYZ, double[], double[], double[]) - Constructor for class com.imsl.chart3d.Surface
Creates a surface from a scattered set of 3D points.
Surface(AxisXYZ, double[], double[], double[], Color[]) - Constructor for class com.imsl.chart3d.Surface
Creates a surface from a scattered set of 3D points with a color given at each point.
Surface.ZFunction - Interface in com.imsl.chart3d
Functional representation of a surface.
SURFACE_TYPE_FLAT - Static variable in class com.imsl.chart3d.Surface
Draws the surface using flat shading.
SURFACE_TYPE_GOURAUD - Static variable in class com.imsl.chart3d.Surface
Draws the surface using Gouraud shading.
SURFACE_TYPE_MESH - Static variable in class com.imsl.chart3d.Surface
Draws the surface as a mesh.
SURFACE_TYPE_NICEST - Static variable in class com.imsl.chart3d.Surface
Draws the surface using the best shading available.
SVD - Class in com.imsl.math
Singular Value Decomposition (SVD) of a rectangular matrix of type double.
SVD(double[][], double) - Constructor for class com.imsl.math.SVD
Construct the singular value decomposition of a rectangular matrix with a given tolerance.
SVD(double[][]) - Constructor for class com.imsl.math.SVD
Construct the singular value decomposition of a rectangular matrix with default tolerance.
SVD.DidNotConvergeException - Exception in com.imsl.math
The iteration did not converge
SVD.DidNotConvergeException(String) - Constructor for exception com.imsl.math.SVD.DidNotConvergeException
 
SVD.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.math.SVD.DidNotConvergeException
 
syd(double, double, int, int) - Static method in class com.imsl.finance.Finance
Returns the depreciation of an asset using the sum-of-years digits method.
SymEigen - Class in com.imsl.math
Computes the eigenvalues and eigenvectors of a real symmetric matrix.
SymEigen(double[][]) - Constructor for class com.imsl.math.SymEigen
Constructs the eigenvalues and the eigenvectors for a real symmetric matrix.
SymEigen(double[][], boolean) - Constructor for class com.imsl.math.SymEigen
Constructs the eigenvalues and (optionally) the eigenvectors for a real symmetric matrix.

T

TableMultiWay - Class in com.imsl.stat
Tallies observations into a multi-way frequency table.
TableMultiWay(double[][], int) - Constructor for class com.imsl.stat.TableMultiWay
Constructor for TableMultiWay.
TableMultiWay(double[][], int[]) - Constructor for class com.imsl.stat.TableMultiWay
Constructor for TableMultiWay.
TableMultiWay.BalancedTable - Class in com.imsl.stat
Tallies the number of unique values of each variable.
TableMultiWay.UnbalancedTable - Class in com.imsl.stat
Tallies the frequency of each cell in x.
TableOneWay - Class in com.imsl.stat
Class TableOneWay calculates a frequency table for a data array.
TableOneWay(double[], int) - Constructor for class com.imsl.stat.TableOneWay
Constructor for TableOneWay.
TableTwoWay - Class in com.imsl.stat
Class TableTwoWay calculates a two-dimensional frequency table for a data array based upon two variables.
TableTwoWay(double[], int, double[], int) - Constructor for class com.imsl.stat.TableTwoWay
Constructor for TableTwoWay.
tan(Complex) - Static method in class com.imsl.math.Complex
Returns the tangent of a Complex.
tan(double) - Static method in class com.imsl.math.JMath
Returns the tangent of a double.
TANH - Static variable in interface com.imsl.datamining.neural.Activation
The hyperbolic tangent activation function, g(x)=tanh{x}=
  frac{e^x-e^{-x}}{e^x+e^{-x}}.
tanh(Complex) - Static method in class com.imsl.math.Complex
Returns the hyperbolic tanh of a Complex.
tanh(double) - Static method in class com.imsl.math.Hyperbolic
Returns the hyperbolic tangent of its argument.
tbilleq(GregorianCalendar, GregorianCalendar, double) - Static method in class com.imsl.finance.Bond
Returns the bond-equivalent yield of a Treasury bill.
tbillprice(GregorianCalendar, GregorianCalendar, double) - Static method in class com.imsl.finance.Bond
Returns the price, per $100 face value, of a Treasury bill.
tbillyield(GregorianCalendar, GregorianCalendar, double) - Static method in class com.imsl.finance.Bond
Returns the yield of a Treasury bill.
TEMPERATURE - Static variable in class com.imsl.math.Physical
 
TEMPORARY_CHANGE - Static variable in class com.imsl.stat.ARMAOutlierIdentification
Indicates detection of a temporary change outlier.
TEMPORARY_CHANGE - Static variable in class com.imsl.stat.AutoARIMA
Indicates detection of a temporary change outlier.
terminal(double) - Method in interface com.imsl.math.FeynmanKac.Boundaries
Returns the terminal condition value.
TEXT - Static variable in class com.imsl.chart.Draw
 
Text - Class in com.imsl.chart
The value of the attribute "Title".
Text(String) - Constructor for class com.imsl.chart.Text
Construct a Text object.
Text(String, int) - Constructor for class com.imsl.chart.Text
Construct a Text object with specified alignment.
Text(Format, double) - Constructor for class com.imsl.chart.Text
Creates a text object by applying a java.text.Format to a double.
TEXT_X_CENTER - Static variable in class com.imsl.chart.ChartNode
Value for attribute "TextAlignment" indicating that the text should be centered.
TEXT_X_LEFT - Static variable in class com.imsl.chart.ChartNode
Value for attribute "TextAlignment" indicating that the text should be left adjusted.
TEXT_X_RIGHT - Static variable in class com.imsl.chart.ChartNode
Value for attribute "TextAlignment" indicating that the text should be right adjusted.
TEXT_Y_BOTTOM - Static variable in class com.imsl.chart.ChartNode
Value for attribute "TextAlignment" indicating that the text should be drawn on the baseline.
TEXT_Y_CENTER - Static variable in class com.imsl.chart.ChartNode
Value for attribute "TextAlignment" indicating that the text should be vertically centered.
TEXT_Y_TOP - Static variable in class com.imsl.chart.ChartNode
Value for attribute "TextAlignment" indicating that the text should be drawn with the top of the letters touching the top of the drawing region.
textAngle - Variable in class com.imsl.chart.Draw
 
textColor - Variable in class com.imsl.chart.Draw
 
textFont - Variable in class com.imsl.chart.Draw
 
throwIllegalArgumentException(String, String, Object[]) - Static method in class com.imsl.Messages
Throws an IllegalArgumentException with a formatted String argument.
throwIllegalStateException(String, String, Object[]) - Static method in class com.imsl.Messages
Throws an IllegalStateException with a formatted String argument.
TIE_AVERAGE - Static variable in class com.imsl.stat.Ranks
In case of ties, use the average of the scores of the tied observations.
TIE_HIGHEST - Static variable in class com.imsl.stat.Ranks
In case of ties, use the highest score in the group of ties.
TIE_LOWEST - Static variable in class com.imsl.stat.Ranks
In case of ties, use the lowest score in the group of ties.
TIE_RANDOM - Static variable in class com.imsl.stat.Ranks
In case of ties, use one of the group of ties chosen at random.
TIME - Static variable in class com.imsl.math.Physical
 
TimeSeriesClassFilter - Class in com.imsl.datamining.neural
Converts time series data contained within nominal categories to a lagged format for processing by a neural network.
TimeSeriesClassFilter(int) - Constructor for class com.imsl.datamining.neural.TimeSeriesClassFilter
Constructor for TimeSeriesClassFilter.
TimeSeriesFilter - Class in com.imsl.datamining.neural
Converts time series data to a lagged format used as input to a neural network.
TimeSeriesFilter() - Constructor for class com.imsl.datamining.neural.TimeSeriesFilter
Constructor for TimeSeriesClassFilter.
toDenseMatrix() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the sparse matrix as a dense matrix.
toDenseMatrix() - Method in class com.imsl.math.SparseMatrix
Returns the sparse matrix as a dense matrix.
Tokenizer - Class in com.imsl.io
Breaks a line into tokens.
Tokenizer(String, char, boolean) - Constructor for class com.imsl.io.Tokenizer
Creates a Tokenizer.
ToolTip - Class in com.imsl.chart
A ToolTip for a chart element.
ToolTip(ChartNode) - Constructor for class com.imsl.chart.ToolTip
Creates a ToolTip node that enables ToolTips on charts.
toSparseArray() - Method in class com.imsl.math.ComplexSparseMatrix
Returns the sparse matrix in the SparseArray form.
toSparseArray() - Method in class com.imsl.math.SparseMatrix
Returns the sparse matrix in the SparseArray form.
toString() - Method in class com.imsl.chart.AbstractChartNode
Returns the name of this ChartNode
toString() - Method in class com.imsl.math.Complex
Returns a String representation for the specified Complex.
toString() - Method in class com.imsl.math.Physical
Returns a String containing the value and units, if any.
train(double[][], int[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Trains a Naive Bayes classifier for classifying data into one of nClasses target classifications.
train(int[][], int[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Trains a Naive Bayes classifier for classifying data into one of nClasses target classifications.
train(double[][], int[][], int[]) - Method in class com.imsl.datamining.NaiveBayesClassifier
Trains a Naive Bayes classifier for classifying data into one of nClasses target classifications.
train(Trainer, double[][], int[]) - Method in class com.imsl.datamining.neural.BinaryClassification
Trains the classification neural network using supplied trainer and patterns.
train(Network, double[][], double[][]) - Method in class com.imsl.datamining.neural.EpochTrainer
Trains the neural network using supplied training patterns.
train(Network, double[][], double[][]) - Method in class com.imsl.datamining.neural.LeastSquaresTrainer
Trains the neural network using supplied training patterns.
train(Trainer, double[][], int[]) - Method in class com.imsl.datamining.neural.MultiClassification
Trains the classification neural network using supplied training patterns.
train(Network, double[][], double[][]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer
Trains the neural network using supplied training patterns.
train(Network, double[][], double[][]) - Method in interface com.imsl.datamining.neural.Trainer
Trains the neural network using supplied training patterns.
Trainer - Interface in com.imsl.datamining.neural
Interface implemented by classes used to train a network.
Transform - Interface in com.imsl.chart
Defines a custom transformation along an axis.
TRANSFORM_ASIN_SQRT - Static variable in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Flag to indicate the arcsine square root transform will be applied to the percentages.
TRANSFORM_CUSTOM - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that the axis using a custom transformation.
TRANSFORM_LINEAR - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that the axis uses linear scaling.
TRANSFORM_LOG - Static variable in class com.imsl.chart.AbstractChartNode
Flag used to indicate that the axis uses logarithmic scaling.
TRANSFORM_NONE - Static variable in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Flag to indicate no transformation of percentages.
TRANSFORM_SQRT - Static variable in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Flag to indicate the square root transform will be applied to the percentages.
TransformDate - Class in com.imsl.chart
Defines a transformation along an axis that skips weekend dates.
TransformDate() - Constructor for class com.imsl.chart.TransformDate
 
translate(int, int) - Method in class com.imsl.chart.Draw
Translates the origin to the point (x,y)
translate(int, int) - Method in class com.imsl.chart.DrawMap
Translates the origin to the point (x,y)
translate(int, int) - Method in class com.imsl.chart.DrawPick
Translates the origin to the point (x,y)
transpose(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix
Return the transpose of a Complex matrix.
transpose(double[][]) - Static method in class com.imsl.math.Matrix
Return the transpose of a matrix.
transpose() - Method in class com.imsl.math.SparseMatrix
Returns the transpose of the matrix.
Treemap - Class in com.imsl.chart
Treemap creates a chart from two arrays of double precision values or one data array and one array of Color values.
Treemap(AxisXY, double[], Color[]) - Constructor for class com.imsl.chart.Treemap
Constructs a treemap using supplied data and colors array.
Treemap(AxisXY, double[], double[], Colormap) - Constructor for class com.imsl.chart.Treemap
Constructs a treemap using supplied data and a colormap.
Treemap.Legend - Class in com.imsl.chart
A legend for use with a treemap.
trim() - Method in class com.imsl.chart3d.BufferedPaint
Returns a subimage with the white space trimmed off.
TUKEY - Static variable in class com.imsl.stat.ANOVA
The Tukey method
TUKEY_KRAMER - Static variable in class com.imsl.stat.ANOVA
The Tukey-Kramer method

U

UChart - Class in com.imsl.chart.qc
UChart is a u-chart for monitoring the defect rate when defects are rare.
UChart(AxisXY, double, int[]) - Constructor for class com.imsl.chart.qc.UChart
Creates a u-Chart given the number of defects for a series of samples with equal sample sizes.
UChart(AxisXY, double[], int[]) - Constructor for class com.imsl.chart.qc.UChart
Creates a u-Chart given the number of defects rates for a series of samples with varying sample sizes.
UNABLE_TO_IDENTIFY - Static variable in class com.imsl.stat.ARMAOutlierIdentification
Indicates detection of an outlier that cannnot be categorized.
UNABLE_TO_IDENTIFY - Static variable in class com.imsl.stat.AutoARIMA
Indicates detection of an outlier that cannnot be categorized.
UNBOUNDED_Z_SCORE_SCALING_MEAN_STDEV - Static variable in class com.imsl.datamining.neural.ScaleFilter
Flag to indicate unbounded z-score scaling using the mean and standard deviation.
UNBOUNDED_Z_SCORE_SCALING_MEDIAN_MAD - Static variable in class com.imsl.datamining.neural.ScaleFilter
Flag to indicate unbounded z-score scaling using the median and mean absolute difference.
uniform(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the uniform cumulative probability distribution function.
uniform(double, double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the uniform cumulative probability distribution function.
unitsString() - Method in class com.imsl.math.Physical
Returns a String containing the units only.
unordered(double, double) - Static method in class com.imsl.math.IEEE
Unordered test on a pair of doubles.
UnsupervisedNominalFilter - Class in com.imsl.datamining.neural
Converts nominal data into a series of binary encoded columns for input to a neural network.
UnsupervisedNominalFilter(int) - Constructor for class com.imsl.datamining.neural.UnsupervisedNominalFilter
Constructor for UnsupervisedNominalFilter.
UnsupervisedOrdinalFilter - Class in com.imsl.datamining.neural
Encodes ordinal data into percentages for input to a neural network.
UnsupervisedOrdinalFilter(int, int) - Constructor for class com.imsl.datamining.neural.UnsupervisedOrdinalFilter
Constructor for UnsupervisedOrdinalFilter.
UNWEIGHTED_LEAST_SQUARES - Static variable in class com.imsl.stat.FactorAnalysis
Indicates unweighted least squares method.
update(Graphics) - Method in class com.imsl.chart.Chart
 
update() - Method in class com.imsl.chart3d.Data
Update the surface by reevaluation of the z-function and the color function.
update(double[]) - Method in class com.imsl.math.Cholesky
Updates the factorization by adding a rank-1 matrix.
update(double[], double) - Method in class com.imsl.math.RadialBasis
Adds a data point with weight = 1.
update(double[], double, double) - Method in class com.imsl.math.RadialBasis
Adds a data point with a specified weight.
update(double[][], double[]) - Method in class com.imsl.math.RadialBasis
Adds a set of data points, all with weight = 1.
update(double[][], double[], double[]) - Method in class com.imsl.math.RadialBasis
Adds a set of data points with user-specified weights.
update(double[]) - Method in class com.imsl.stat.ChiSquaredTest
Adds new observations to the test.
update(double) - Method in class com.imsl.stat.ChiSquaredTest
Adds a new observation to the test.
update(double[], double[]) - Method in class com.imsl.stat.ChiSquaredTest
Adds new observations to the test.
update(double, double) - Method in class com.imsl.stat.ChiSquaredTest
Adds a new observation to the test.
update(double[][], int[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Trains a set of observations and associated frequencies and weights by performing a linear or quadratic discriminant function analysis among several known groups.
update(double[][], int[], int[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Trains a set of observations and associated frequencies and weights by performing a linear or quadratic discriminant function analysis among several known groups.
update(double[][], int[], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Trains a set of observations and associated frequencies and weights by performing a linear or quadratic discriminant function analysis among several known groups.
update(double[][], int[], int[], int[], double[]) - Method in class com.imsl.stat.DiscriminantAnalysis
Trains a set of observations and associated frequencies and weights by performing a linear or quadratic discriminant function analysis among several known groups.
update(double[], double[][], double[][]) - Method in class com.imsl.stat.KalmanFilter
Performs computation of the update equations.
update(double[], double) - Method in class com.imsl.stat.LinearRegression
Updates the regression object with a new observation.
update(double[], double, double) - Method in class com.imsl.stat.LinearRegression
Updates the regression object with a new observation and weight.
update(double[][], double[]) - Method in class com.imsl.stat.LinearRegression
Updates the regression object with a new set of observations.
update(double[][], double[], double[]) - Method in class com.imsl.stat.LinearRegression
Updates the regression object with a new set of observations and weights.
update(double[], double[]) - Method in class com.imsl.stat.NormTwoSample
Concatenates samples x and y to the samples provided in the constructor.
update(double) - Method in class com.imsl.stat.Summary
Adds an observation to the Summary object.
update(double, double) - Method in class com.imsl.stat.Summary
Adds an observation and associated weight to the Summary object.
update(double[]) - Method in class com.imsl.stat.Summary
Adds a set of observations to the Summary object.
update(double[], double[]) - Method in class com.imsl.stat.Summary
Adds a set of observations and associated weights to the Summary object.
update(double, double, double) - Method in class com.imsl.stat.UserBasisRegression
Adds a new observation and associated weight to the RegressionBasis object.
updateArray(String, Array) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an Array value.
updateArray(int, Array) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an Array value.
updateAsciiStream(int, InputStream, int) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an ascii stream value.
updateAsciiStream(String, InputStream, int) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an ascii stream value.
updateBigDecimal(int, BigDecimal) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a java.math.BigDecimal value.
updateBigDecimal(String, BigDecimal) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a java.sql.BigDecimal value.
updateBinaryStream(int, InputStream, int) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a binary stream value.
updateBinaryStream(String, InputStream, int) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a binary stream value.
updateBlob(int, Blob) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an java.sql.Blob value.
updateBlob(String, Blob) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an java.sql.Blob value.
updateBoolean(int, boolean) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a boolean value.
updateBoolean(String, boolean) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a boolean value.
updateByte(int, byte) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a byte value.
updateByte(String, byte) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a byte value.
updateBytes(int, byte[]) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a byte array value.
updateBytes(String, byte[]) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a byte value.
updateCharacterStream(int, Reader, int) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a character stream value.
updateCharacterStream(String, Reader, int) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a character stream value.
updateClob(String, Clob) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an java.sql.Clob value.
updateClob(int, Clob) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an java.sql.Clob value.
updateDate(int, Date) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a java.sql.Date value.
updateDate(String, Date) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a java.sql.Date value.
updateDouble(int, double) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a double value.
updateDouble(String, double) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a double value.
updateFloat(int, float) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a float value.
updateFloat(String, float) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a float value.
updateInt(int, int) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an int value.
updateInt(String, int) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an int value.
updateLong(int, long) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a long value.
updateLong(String, long) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a long value.
updateNull(int) - Method in class com.imsl.io.AbstractFlatFile
Gives a nullable column a null value.
updateNull(String) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a null value.
updateObject(int, Object, int) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an Object value.
updateObject(int, Object) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an Object value.
updateObject(String, Object, int) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an Object value.
updateObject(String, Object) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an Object value.
updateRef(String, Ref) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an java.sql.Ref value.
updateRef(int, Ref) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with an java.sql.Ref value.
updateRow() - Method in class com.imsl.io.AbstractFlatFile
Updates the underlying database with the new contents of the current row of this ResultSet object.
updateShort(int, short) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a short value.
updateShort(String, short) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a short value.
updateString(int, String) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a String value.
updateString(String, String) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a String value.
updateTime(int, Time) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a java.sql.Time value.
updateTime(String, Time) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a java.sql.Time value.
updateTimestamp(int, Timestamp) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a java.sql.Timestamp value.
updateTimestamp(String, Timestamp) - Method in class com.imsl.io.AbstractFlatFile
Updates the designated column with a java.sql.Timestamp value.
updateX(double[]) - Method in class com.imsl.stat.NormTwoSample
Concatenates the values in x to the first sample provided in the constructor.
updateY(double[]) - Method in class com.imsl.stat.NormTwoSample
Concatenates the values in y to the second sample provided in the constructor.
UPPER_TRIANGULAR - Static variable in class com.imsl.math.PrintMatrix
This flag as the argument to setMatrixType, indicates that only the upper triangular elements of the matrix are to be printed.
UserBasisRegression - Class in com.imsl.stat
Fits a linear function of the form y = c_0  + c_1 f_1 (x) + c_2 f_2 (x) +  cdots  + c_k f_k (x) + varepsilon, where f_1 (x),f_2 (x), cdots ,f_k (x) are the user basis functions f_i (x) evaluated at index values i = 1,2, ldots ,k,c_0 is the intercept, c_1 ,c_2 , cdots ,c_k are the coefficients associated with the basis functions, and is the random error associated with y.
UserBasisRegression(RegressionBasis, int, boolean) - Constructor for class com.imsl.stat.UserBasisRegression
Constructs a UserBasisRegression object

V

validateLink(Node, Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork
Checks that a Link between two Nodes is valid.
value(double) - Method in class com.imsl.math.BSpline
Returns the value of the B-spline at a point.
value(double[]) - Method in class com.imsl.math.BSpline
Returns the value of the B-spline at each point of an array.
value - Variable in class com.imsl.math.Physical
 
value(double[]) - Method in class com.imsl.math.RadialBasis
Returns the value of the radial basis approximation at a point.
value(double[][]) - Method in class com.imsl.math.RadialBasis
Returns the value of the radial basis at a point.
value(double) - Method in class com.imsl.math.Spline
Returns the value of the spline at a point.
value(double[]) - Method in class com.imsl.math.Spline
Returns the value of the spline at each point of an array.
value(double, double) - Method in class com.imsl.math.Spline2D
Returns the value of the tensor-product spline at the point (x, y).
value(double[], double[]) - Method in class com.imsl.math.Spline2D
Returns the values of the tensor-product spline of an array of points.
valueOf(String) - Static method in class com.imsl.math.Complex
Parses a String into a Complex.
values - Variable in class com.imsl.math.ComplexSparseMatrix.SparseArray
Jagged array containing sparse array values.
values - Variable in class com.imsl.math.SparseMatrix.SparseArray
Jagged array containing sparse array values.
variance(double[]) - Static method in class com.imsl.stat.Summary
Returns the population variance of the given data set.
variance(double[], double[]) - Static method in class com.imsl.stat.Summary
Returns the population variance of the given data set and associated weights.
VARIANCE_COVARIANCE_MATRIX - Static variable in class com.imsl.stat.Covariances
Indicates variance-covariance matrix.
VARIANCE_COVARIANCE_MATRIX - Static variable in class com.imsl.stat.FactorAnalysis
Indicates variance-covariance matrix.
vdb(double, double, int, int, int, double, boolean) - Static method in class com.imsl.finance.Finance
Returns the depreciation of an asset for any given period using the variable-declining balance method.
Version - Class in com.imsl
Print the version information.
Version() - Constructor for class com.imsl.Version
 
verticalStripe(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint
Returns a vertically striped pattern.
vnorm(double[], double[], double[]) - Method in class com.imsl.math.ODE
Returns the norm of a vector.

W

warning(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML
Receive notification of a warning.
Warning - Class in com.imsl
Handle warning messages.
Warning() - Constructor for class com.imsl.Warning
 
WarningObject - Class in com.imsl
Handle warning messages.
WarningObject() - Constructor for class com.imsl.WarningObject
 
wasNull() - Method in class com.imsl.io.AbstractFlatFile
Reports whether the last column read had a value of SQL NULL.
WB_LINEAR - Static variable in interface com.imsl.chart.Colormap
Black and white (grayscale) colormap, the reverse of BW_LINEAR.
WebSafeImageFilter - Class in com.imsl.chart
Maps colors in an image to the nearest Web-safe color.
WebSafeImageFilter() - Constructor for class com.imsl.chart.WebSafeImageFilter
 
Weibull(double, double, double) - Static method in class com.imsl.stat.Cdf
Evaluates the Weibull cumulative probability distribution function.
Weibull(double, double, double) - Static method in class com.imsl.stat.InvCdf
Returns the inverse of the Weibull cumulative probability distribution function.
Weibull(double, double, double) - Static method in class com.imsl.stat.Pdf
Evaluates the Weibull probability density function.
weight - Variable in class com.imsl.math.BsLeastSquares
The weight array of length n, where n is the number of data points fit.
WilcoxonRankSum - Class in com.imsl.stat
Performs a Wilcoxon rank sum test.
WilcoxonRankSum(double[], double[]) - Constructor for class com.imsl.stat.WilcoxonRankSum
Constructor for WilcoxonRankSum.
write(String, String) - Method in class com.imsl.chart3d.Canvas3DChart
Write the canvas as an image file after it is next redrawn.
writePNG(OutputStream, int, int) - Method in class com.imsl.chart.Chart
Writes the chart as an PNG file.
writeSVG(Writer, boolean) - Method in class com.imsl.chart.Chart
Writes the chart as an SVG file.

X

XbarR - Class in com.imsl.chart.qc
XbarR is an X-bar chart for monitoring a process using sample ranges.
XbarR(AxisXY, double[][]) - Constructor for class com.imsl.chart.qc.XbarR
Creates an X-bar chart from sample data using sample ranges.
XbarR(AxisXY, int, double[], double[]) - Constructor for class com.imsl.chart.qc.XbarR
Creates an X-bar control chart given the means and ranges for a series of equally sized samples.
XbarR(AxisXY, int[], double[], double[]) - Constructor for class com.imsl.chart.qc.XbarR
Creates an X-bar control chart given the means and ranges for a series of unequally sized samples.
XbarS - Class in com.imsl.chart.qc
XbarS is an X-bar chart for monitoring a process using sample standard deviations.
XbarS(AxisXY, double[][]) - Constructor for class com.imsl.chart.qc.XbarS
Creates an XbarS chart from sample data using within sample standard deviations.
XbarS(AxisXY, int, double[], double[]) - Constructor for class com.imsl.chart.qc.XbarS
Creates an XbarS chart given the means and standard deviations for a series of equally sized samples.
XbarS(AxisXY, int[], double[], double[]) - Constructor for class com.imsl.chart.qc.XbarS
Creates an XbarS chart given the means and standard deviations for a series of unequally sized samples.
xirr(double[], Date[]) - Static method in class com.imsl.finance.Finance
Returns the internal rate of return for a schedule of cash flows.
xirr(double[], Date[], double) - Static method in class com.imsl.finance.Finance
Returns the internal rate of return for a schedule of cash flows with a user supplied initial guess.
XmR - Class in com.imsl.chart.qc
XmR is an XmR chart for monitoring a process using moving ranges.
XmR(AxisXY, double[]) - Constructor for class com.imsl.chart.qc.XmR
Creates an XmR chart given sample data.
xnpv(double, double[], Date[]) - Static method in class com.imsl.finance.Finance
Returns the present value for a schedule of cash flows.

Y

Y(double, double, int) - Static method in class com.imsl.math.Bessel
Evaluate a sequence of Bessel functions of the second kind with real nonnegative order and real positive argument.
yearfrac(GregorianCalendar, GregorianCalendar, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the fraction of a year represented by the number of whole days between two dates.
yield(GregorianCalendar, GregorianCalendar, double, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the yield of a security that pays periodic interest.
yielddisc(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the annual yield of a discount bond.
yieldmat(GregorianCalendar, GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond
Returns the annual yield of a security that pays interest at maturity.

Z

ZeroPolynomial - Class in com.imsl.math
The ZeroPolynomial class computes the zeros of a polynomial with complex coefficients, Aberth's method.
ZeroPolynomial() - Constructor for class com.imsl.math.ZeroPolynomial
Creates an instance of the solver.
ZeroPolynomial.DidNotConvergeException - Exception in com.imsl.math
The iteration did not converge
ZeroPolynomial.DidNotConvergeException(String) - Constructor for exception com.imsl.math.ZeroPolynomial.DidNotConvergeException
 
ZeroPolynomial.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.math.ZeroPolynomial.DidNotConvergeException
 
ZerosFunction - Class in com.imsl.math
Finds the real zeros of a real, continuous, univariate function, f(x).
ZerosFunction() - Constructor for class com.imsl.math.ZerosFunction
Creates an instance of the solver.
ZerosFunction.Function - Interface in com.imsl.math
Public interface for the user supplied function to ZerosFunction.
ZeroSystem - Class in com.imsl.math
Solves a system of n nonlinear equations f(x) = 0 using a modified Powell hybrid algorithm.
ZeroSystem(int) - Constructor for class com.imsl.math.ZeroSystem
Creates an object to find the zeros of a system of n equations.
ZeroSystem.DidNotConvergeException - Exception in com.imsl.math
The iteration did not converge.
ZeroSystem.DidNotConvergeException(String) - Constructor for exception com.imsl.math.ZeroSystem.DidNotConvergeException
 
ZeroSystem.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.math.ZeroSystem.DidNotConvergeException
 
ZeroSystem.Function - Interface in com.imsl.math
Public interface for user supplied function to ZeroSystem object.
ZeroSystem.Jacobian - Interface in com.imsl.math
Public interface for user supplied function to ZeroSystem object.
ZeroSystem.ToleranceTooSmallException - Exception in com.imsl.math
Tolerance too small
ZeroSystem.ToleranceTooSmallException(String, Object[]) - Constructor for exception com.imsl.math.ZeroSystem.ToleranceTooSmallException
 
ZeroSystem.TooManyIterationsException - Exception in com.imsl.math
Too many iterations.
ZeroSystem.TooManyIterationsException() - Constructor for exception com.imsl.math.ZeroSystem.TooManyIterationsException
 
ZeroSystem.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.math.ZeroSystem.TooManyIterationsException
 
ZeroSystem.TooManyIterationsException(Object[]) - Constructor for exception com.imsl.math.ZeroSystem.TooManyIterationsException
 

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JMSLTM Numerical Library 6.1

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Built July 30 2010.