Uses of Package
com.imsl.stat

Packages that use com.imsl.stat

Package	Description
com.imsl.datamining	Data mining and machine learning.
com.imsl.datamining.neural	Neural networks.
com.imsl.math	Mathematical functions and algorithms.
com.imsl.stat	Statistical methods.
com.imsl.stat.distributions	Probability distributions and parameter estimation.
com.imsl.test.example.datamining	Data mining examples.
com.imsl.test.example.stat	Statistics examples.

Classes in com.imsl.stat used by com.imsl.datamining

Class and Description
ProbabilityDistribution Public interface for a user-supplied probability distribution.
Random Generate uniform and non-uniform random number distributions.

Classes in com.imsl.stat used by com.imsl.datamining.neural

Class and Description
Random Generate uniform and non-uniform random number distributions.

Classes in com.imsl.stat used by com.imsl.math

Class and Description
ANOVA Analysis of Variance table and related statistics.
Random Generate uniform and non-uniform random number distributions.
RandomSequence Interface implemented by generators of random or quasi-random multidimensional sequences.

Classes in com.imsl.stat used by com.imsl.stat

Class and Description
ANOVA Analysis of Variance table and related statistics.
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.ResidualsTooLargeException The residuals have become too large in one step of the Least Squares estimation of the ARMA coefficients.
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.NonInvertibleException The solution is noninvertible.
ARMAMaxLikelihood.NonStationaryException The solution is nonstationary.
AutoARIMA.NoAcceptableModelFoundException No appropriate ARIMA model could be found.
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.
CategoricalGenLinModel.RankDeficientException The model has been determined to be rank deficient.
CdfFunction Public interface for the user-supplied cumulative distribution function to be used by InverseCdf and ChiSquaredTest.
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.
Covariances.DiffObsDeletedException Deprecated.
Covariances.MoreObsDelThanEnteredException Deprecated.
Covariances.NonnegativeFreqException Frequencies must be nonnegative.
Covariances.NonnegativeWeightException Weights must be nonnegative.
Covariances.TooManyObsDeletedException Deprecated.
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.
Distribution Public interface for the user-supplied distribution function.
ExtendedGARCH Abstract class for extended GARCH models.
ExtendedGARCH.Solver An enumeration of the types of solvers available to the estimation procedure.
ExtendedGARCH.zDistribution Public interface for specifying the distribution of \(z_t\).
FactorAnalysis.BadVarianceException Bad variance error.
FactorAnalysis.EigenvalueException Eigenvalue error.
FactorAnalysis.NonPositiveEigenvalueException Non positive eigenvalue error.
FactorAnalysis.NotPositiveDefiniteException 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.ScoreMethod Indicates which method is used for computing the factor score coefficients.
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
LinearRegression.CaseStatistics 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 Contains statistics related to the regression coefficients.
MultiCrossCorrelation.NonPosVariancesException The problem is ill-conditioned.
MultidimensionalScaling Performs metric multidimensional scaling using the Euclidean or individual differences model.
MultidimensionalScaling.IllDefinedHessianException A Hessian matrix is ill-defined.
MultidimensionalScaling.NotEnoughPositiveEigenvaluesException The number of positive eigenvalues of the double-centered distance matrix is too small.
NonlinearRegression.Function Public interface for the user supplied function for NonlinearRegression.
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.
PartialCovariances.InvalidMatrixException Exception thrown if a computed correlation is greater than one for some pair of variables.
PartialCovariances.InvalidPartialCorrelationException Exception thrown if a computed partial correlation is greater than one for some pair of variables.
Pdf.AltSeriesAccuracyLossException The magnitude of alternating series sum is too small relative to the sum of positive terms to permit a reliable accuracy.
ProbabilityDistribution Public interface for a user-supplied probability distribution.
ProportionalHazards.ClassificationVariableLimitException The Classification Variable limit set by the user through setUpperBound has been exceeded.
Random Generate uniform and non-uniform random number distributions.
Random.BaseGenerator Base pseudorandom number.
RandomSequence Interface implemented by generators of random or quasi-random multidimensional sequences.
RegressionBasis Public interface for user supplied function to UserBasisRegression object.
SelectionRegression.NoVariablesException No Variables can enter the model.
SelectionRegression.Statistics Statistics contains statistics related to the regression coefficients.
StepwiseRegression.CoefficientTTests CoefficientTTests() contains statistics related to the student-t test, for each regression coefficient.
StepwiseRegression.CyclingIsOccurringException Cycling is occurring.
StepwiseRegression.NoVariablesEnteredException No Variables can enter the model.
TableMultiWay.BalancedTable Tallies the number of unique values of each variable.
TableMultiWay.UnbalancedTable Tallies the frequency of each cell in x.
TimeSeries A specialized class for time series data and analysis.
TimeSeriesOperations.CombineMethod Public enum of methods for combining synchronous time series values.
TimeSeriesOperations.Function Public interface for the user-supplied function that defines how to combine two synchronous time series values.
TimeSeriesOperations.MergeRule Public enum of merge rules that defines how two time series should be merged.
WelchsTTest.Hypothesis The form of the alternate hypothesis.

Classes in com.imsl.stat used by com.imsl.stat.distributions

Class and Description
Random Generate uniform and non-uniform random number distributions.

Classes in com.imsl.stat used by com.imsl.test.example.datamining

Class and Description
Distribution Public interface for the user-supplied distribution function.
ProbabilityDistribution Public interface for a user-supplied probability distribution.

Classes in com.imsl.stat used by com.imsl.test.example.stat

Class and Description
CdfFunction Public interface for the user-supplied cumulative distribution function to be used by InverseCdf and ChiSquaredTest.