Package com.imsl.stat

Interface Summary

CdfFunction	Public interface for the user-supplied cumulative distribution function to be used by InverseCdf and ChiSquaredTest.
NonlinearRegression.Derivative	Public interface for the user supplied function to compute the derivative for NonlinearRegression.
NonlinearRegression.Function	Public interface for the user supplied function for NonlinearRegression.
Random.BaseGenerator	Base pseudorandom number.
RandomSequence	Interface implemented by generators of random or quasi-random multidimension sequences.
RegressionBasis	Public interface for user supplied function to UserBasisRegression object.

Class Summary

ANOVA	Analysis of Variance table and related statistics.
ANOVAFactorial	Analyzes a balanced factorial design with fixed effects.
ARAutoUnivariate	Automatically determines the best autoregressive time series model using Akaike's Information Criterion.
ARAutoUnivariate.Formatter	Simple formatter for ARAutoUnivariate logging
ARMA	Computes least-square estimates of parameters for an ARMA model.
ARMAEstimateMissing	Estimates missing values in a time series collected with equal spacing.
ARMAMaxLikelihood	Computes maximum likelihood estimates of parameters for an ARMA model with p and q autoregressive and moving average terms respectively.
ARSeasonalFit	Estimates the optimum seasonality parameters for a time series using an autoregressive model, AR(p), to represent the time series.
AutoCorrelation	Computes the sample autocorrelation function of a stationary time series.
CategoricalGenLinModel	Analyzes categorical data using logistic, probit, Poisson, and other linear models.
Cdf	Cumulative probability distribution functions, probability density functions, and their inverses.
ChiSquaredTest	Chi-squared goodness-of-fit test.
ClusterHierarchical	Performs a hierarchical cluster analysis from a distance matrix.
ClusterKMeans	Perform a K-means (centroid) cluster analysis.
ContingencyTable	Performs a chi-squared analysis of a two-way contingency table.
Covariances	Computes the sample variance-covariance or correlation matrix.
CrossCorrelation	Computes the sample cross-correlation function of two stationary time series.
Difference	Differences a seasonal or nonseasonal time series.
DiscriminantAnalysis	Performs a linear or a quadratic discriminant function analysis among several known groups and the use of either reclassification, split sample, or the leaving-out-one methods in order to evaluate the rule.
Dissimilarities	Computes a matrix of dissimilarities (or similarities) between the columns (or rows) of a matrix.
EmpiricalQuantiles	Computes empirical quantiles.
FactorAnalysis	Performs Principal Component Analysis or Factor Analysis on a covariance or correlation matrix.
FaureSequence	Generates the low-discrepancy Faure sequence.
GARCH	Computes estimates of the parameters of a GARCH(p,q) model.
InverseCdf	Inverse of user-supplied cumulative distribution function.
KalmanFilter	Performs Kalman filtering and evaluates the likelihood function for the state-space model.
KaplanMeierECDF	Computes the Kaplan-Meier reliability function estimates or the CDF based on failure data that may be multi-censored.
KolmogorovOneSample	The class KolmogorovOneSample performs a Kolmogorov-Smirnov goodness-of-fit test in one sample.
KolmogorovTwoSample	Performs a Kolmogorov-Smirnov two-sample test.
LinearRegression	Fits a multiple linear regression model with or without an intercept.
MersenneTwister	A 32-bit Mersenne Twister generator.
MersenneTwister64	A 64-bit Mersenne Twister generator.
MultiCrossCorrelation	Computes the multichannel cross-correlation function of two mutually stationary multichannel time series.
MultipleComparisons	Performs Student-Newman-Keuls multiple comparisons test.
NonlinearRegression	Fits a multivariate nonlinear regression model using least squares.
NormalityTest	Performs a test for normality.
NormOneSample	Computes statistics for mean and variance inferences using a sample from a normal population.
NormTwoSample	Computes statistics for mean and variance inferences using samples from two normal populations.
Random	Generate uniform and non-uniform random number distributions.
Ranks	Compute the ranks, normal scores, or exponential scores for a vector of observations.
RegressorsForGLM	Generates regressors for a general linear model.
SelectionRegression	Selects the best multiple linear regression models.
SignTest	Performs a sign test.
Sort	A collection of sorting functions.
StepwiseRegression	Builds multiple linear regression models using forward selection, backward selection, or stepwise selection.
Summary	Computes basic univariate statistics.
TableMultiWay	Tallies observations into a multi-way frequency table.
TableOneWay	Class TableOneWay calculates a frequency table for a data array.
TableTwoWay	Class TableTwoWay calculates a two-dimensional frequency table for a data array based upon two variables.
UserBasisRegression	Fits a linear function of the form , where are the user basis functions evaluated at index values is the intercept, are the coefficients associated with the basis functions, and is the random error associated with y.
WilcoxonRankSum	Performs a Wilcoxon rank sum test.

Exception Summary

ARAutoUnivariate.TriangularMatrixSingularException	The input triangular matrix is singular.
ARMA.IllConditionedException	The problem is ill-conditioned.
ARMA.IncreaseErrRelException	The bound for the relative error is too small.
ARMA.MatrixSingularException	The input matrix is singular.
ARMA.NewInitialGuessException	The iteration has not made good progress.
ARMA.TooManyCallsException	The number of calls to the function has exceeded the maximum number of iterations times the number of moving average (MA) parameters + 1.
ARMA.TooManyFcnEvalException	Maximum number of function evaluations exceeded.
ARMA.TooManyITNException	Maximum number of iterations exceeded.
ARMA.TooManyJacobianEvalException	Maximum number of Jacobian evaluations exceeded.
ARMAMaxLikelihood.InitialMAException	The initial values for the moving average parameters are not invertible.
ARMAMaxLikelihood.NonInvertibleException	The solution is noninvertible.
ARMAMaxLikelihood.NonStationaryException	The solution is nonstationary.
AutoCorrelation.NonPosVariancesException	The problem is ill-conditioned.
CategoricalGenLinModel.ClassificationVariableException	The ClassificationVariable vector has not been initialized.
CategoricalGenLinModel.ClassificationVariableLimitException	The Classification Variable limit set by the user through setUpperBound has been exceeded.
CategoricalGenLinModel.ClassificationVariableValueException	The number of distinct values for each Classification Variable must be greater than 1.
CategoricalGenLinModel.DeleteObservationsException	The number of observations to be deleted (set by setObservationMax) has grown too large.
ChiSquaredTest.DidNotConvergeException	The iteration did not converge
ChiSquaredTest.NoObservationsException	There are no observations.
ChiSquaredTest.NotCDFException	The function is not a Cumulative Distribution Function (CDF).
ClusterKMeans.ClusterNoPointsException	There is a cluster with no points
ClusterKMeans.NoConvergenceException	Convergence did not occur within the maximum number of iterations.
ClusterKMeans.NonnegativeFreqException	Frequencies must be nonnegative.
ClusterKMeans.NonnegativeWeightException	Weights must be nonnegative.
Covariances.DiffObsDeletedException	Different observations are being deleted from return matrix than were originally entered.
Covariances.MoreObsDelThanEnteredException	More observations are being deleted from the output covariance matrix than were originally entered (the corresponding row, column of the incidence matrix is less than zero).
Covariances.NonnegativeFreqException	Frequencies must be nonnegative.
Covariances.NonnegativeWeightException	Weights must be nonnegative.
Covariances.TooManyObsDeletedException	More observations have been deleted than were originally entered (the sum of frequencies has become negative).
CrossCorrelation.NonPosVariancesException	The problem is ill-conditioned.
DiscriminantAnalysis.CovarianceSingularException	The variance-Covariance matrix is singular.
DiscriminantAnalysis.EmptyGroupException	There are no observations in a group.
DiscriminantAnalysis.SumOfWeightsNegException	The sum of the weights have become negative.
Dissimilarities.NoPositiveVarianceException	No variable has positive variance.
Dissimilarities.ScaleFactorZeroException	The computations cannot continue because a scale factor is zero.
Dissimilarities.ZeroNormException	The computations cannot continue because the Euclidean norm of the column is equal to zero.
EmpiricalQuantiles.ScaleFactorZeroException	The computations cannot continue because a scale factor is zero.
FactorAnalysis.BadVarianceException	Bad variance error.
FactorAnalysis.EigenvalueException	Eigenvalue error.
FactorAnalysis.NoDegreesOfFreedomException	No degrees of freedom error.
FactorAnalysis.NonPositiveEigenvalueException	Non positive eigenvalue error.
FactorAnalysis.NotPositiveDefiniteException	Covariance matrix not positive definite.
FactorAnalysis.NotPositiveSemiDefiniteException	Covariance matrix not positive semi-definite.
FactorAnalysis.NotSemiDefiniteException	Hessian matrix not semi-definite.
FactorAnalysis.RankException	Rank of covariance matrix error.
FactorAnalysis.SingularException	Covariance matrix singular error.
GARCH.ConstrInconsistentException	The equality constraints are inconsistent.
GARCH.EqConstrInconsistentException	The equality constraints and the bounds on the variables are found to be inconsistent.
GARCH.NoVectorXException	No vector X satisfies all of the constraints.
GARCH.TooManyIterationsException	Number of function evaluations exceeded 1000.
GARCH.VarsDeterminedException	The variables are determined by the equality constraints.
InverseCdf.DidNotConvergeException	The iteration did not converge
MultiCrossCorrelation.NonPosVariancesException	The problem is ill-conditioned.
NonlinearRegression.NegativeFreqException	A negative frequency was encountered.
NonlinearRegression.NegativeWeightException	A negative weight was encountered.
NonlinearRegression.TooManyIterationsException	The number of iterations has exceeded the maximum allowed.
NormalityTest.NoVariationInputException	There is no variation in the input data.
SelectionRegression.NoVariablesException	No Variables can enter the model.
StepwiseRegression.CyclingIsOccurringException	Cycling is occurring.
StepwiseRegression.NoVariablesEnteredException	No Variables can enter the model.