Imsl.Stat namespace contains a wide range of statistical classes, including summary statistics, regression, and ANOVA.

Classes

ClassDescription
AllDeletedException
There are no observations.
AllMissingException
There are no observations.
AltSeriesAccuracyLossException
The magnitude of alternating series sum is too small relative to the sum of positive terms to permit a reliable accuracy.
ANCOVA
Analyzes a one-way classification model with covariates.
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.
ARMA
Computes least-square estimates of parameters for an ARMA model.
ARMAEstimateMissing
Estimates missing values in a time series collected with equal spacing. Missing values can be replaced by these estimates prior to fitting a time series using the ARMA class.
ARMAMaxLikelihood
Computes maximum likelihood estimates of parameters for an ARMA model with p and q autoregressive and moving average terms respectively.
ARMAOutlierIdentification
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. This class also allows computation of forecasts.
ARSeasonalFit
Estimates the optimum seasonality parameters for a time series using an autoregressive model, AR(p), to represent the time series.
AutoARIMA
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.
AutoCorrelation
Computes the sample autocorrelation function of a stationary time series.
BadVarianceException
The input variance is not in the allowed range.
CategoricalGenLinModel
Analyzes categorical data using logistic, probit, Poisson, and other linear models.
Cdf
Cumulative probability distribution functions.
ChiSquaredTest
Chi-squared goodness-of-fit test.
ClassificationVariableException
The ClassificationVariable vector has not been initialized.
ClassificationVariableLimitException
The Classification Variable limit set by the user through setUpperBound has been exceeded.
ClassificationVariableValueException
The number of distinct values for each Classification Variable must be greater than 1.
ClusterHierarchical
Performs a hierarchical cluster analysis from a distance matrix.
ClusterKMeans
Perform a K-means (centroid) cluster analysis.
ClusterNoPointsException
There is a cluster with no points.
ConstrInconsistentException
The equality constraints are inconsistent.
ContingencyTable
Performs a chi-squared analysis of a two-way contingency table.
Covariances
Computes the sample variance-covariance or correlation matrix.
CovarianceSingular1Exception
The variance-Covariance matrix is singular.
CovarianceSingular2Exception
The variance-Covariance matrix is singular.
CovarianceSingularException
The variance-Covariance matrix is singular.
CrossCorrelation
Computes the sample cross-correlation function of two stationary time series.
CyclingIsOccurringException
Cycling is occurring.
DeleteObservationsException
The number of observations to be deleted (set by setObservationMax) has grown too large.
DidNotConvergeException
The iteration did not converge.
Difference
Differences a seasonal or nonseasonal time series.
DiffObsDeletedException
Different observations are being deleted from return matrix than were originally entered.
DiscriminantAnalysis
Performs a linear or a quadratic discriminant function analysis among several known groups.
Dissimilarities
Computes a matrix of dissimilarities (or similarities) between the columns (or rows) of a matrix.
EigenvalueException
An error occured in calculating the eigenvalues of the adjusted (inverse) covariance matrix. Check the input covariance matrix.
EmpiricalQuantiles
Computes empirical quantiles.
EmptyGroupException
There are no observations in a group. Cannot compute statistics.
EqConstrInconsistentException
The equality constraints and the bounds on the variables are found to be inconsistent.
FactorAnalysis
Performs Principal Component Analysis or Factor Analysis on a covariance or correlation matrix.
FaureSequence
Generates the low-discrepancy Faure sequence.
GammaDistribution
Evaluates a gamma probability density for a given set of data.
GARCH
Computes estimates of the parameters of a GARCH(p,q) model.
IllConditionedException
The problem is ill-conditioned.
IncreaseErrRelException
The bound for the relative error is too small.
InitialMAException
The initial values for the moving average parameters are not invertable. Execution is halted.
InvalidMatrixException
Exception thrown if a computed correlation is greater than one for some pair of variables.
InvalidPartialCorrelationException
Exception thrown if a computed partial correlation is greater than one for some pair of variables.
InvCdf
Inverse cumulative probability distribution functions.
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.
KaplanMeierEstimates
Computes Kaplan-Meier (or product-limit) estimates of survival probabilities for a sample of failure times that possibly contain right consoring.
KolmogorovOneSample
The class KolmogorovOneSample performs a Kolmogorov-Smirnov goodness-of-fit test in one sample.
KolmogorovTwoSample
Performs a Kolmogorov-Smirnov two-sample test.
LackOfFit
Performs lack-of-fit test for a univariate time series or transfer function given the appropriate correlation function.
LifeTables
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.
LinearRegression
Fits a multiple linear regression model with or without an intercept.
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..::.CoefficientTTestsValue
CoefficientTTestsValue contains statistics related to the regression coefficients.
LogNormalDistribution
Evaluates a lognormal probability density for a given set of data.
MatrixSingularException
The input matrix is singular.
MersenneTwister
A 32-bit Mersenne Twister generator.
MersenneTwister64
A 64-bit Mersenne Twister generator.
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).
MultiCrossCorrelation
Computes the multichannel cross-correlation function of two mutually stationary multichannel time series.
MultipleComparisons
Performs Student-Newman-Keuls multiple comparisons test.
NegativeFreqException
A negative frequency was encountered.
NegativeWeightException
A negative weight was encountered.
NewInitialGuessException
The iteration has not made good progress.
NoAcceptableModelFoundException
No appropriate ARIMA model could be found.
NoConvergenceException
Convergence did not occur within the maximum number of iterations.
NoDegreesOfFreedomException
No degrees of freedom error.
NonInvertibleException
The solution is noninvertible.
NonlinearRegression
Fits a multivariate nonlinear regression model using least squares.
NonPositiveEigenvalueException
Maximum number of iterations exceeded.
NonPosVarianceException
The problem is ill-conditioned.
NonPosVarianceXYException
The problem is ill-conditioned.
NonStationaryException
The solution is nonstationary.
NoPositiveVarianceException
No variable has positive variance. The Mahalanobis distances cannot be computed.
NoProgressException
The algorithm is not making any progress. Try a new initial guess.
NormalDistribution
Evaluates the normal (Gaussian) probability density for a given set of data.
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.
NotCDFException
The function is not a Cumulative Distribution Function (CDF).
NotPositiveDefiniteException
Covariance matrix is not positive definite.
NotPositiveSemiDefiniteException
Covariance matrix is not positive semi-definite.
NotSemiDefiniteException
Hessian matrix is not semi-definite.
NoVariablesEnteredException
No Variables can enter the model.
NoVariablesException
No variables can enter the model.
NoVariationInputException
There is no variation in the input data.
NoVectorXException
No vector X satisfies all of the constraints.
PartialCovariances
Class PartialCovariances computes the partial covariances or partial correlations from an input covariance or correlation matrix.
Pdf
Probability density functions.
PoissonDistribution
Evaluates a Poisson probability density of a given set of data.
PooledCovarianceSingularException
The pooled variance-Covariance matrix is singular.
ProportionalHazards
Analyzes survival and reliability data using Cox's proportional hazards model.
Random
Generate uniform and non-uniform random number distributions.
RankDeficientException
The model has been determined to be rank deficient.
RankException
Rank of covariance matrix error.
Ranks
Compute the ranks, normal scores, or exponential scores for a vector of observations.
RegressorsForGLM
Generates regressors for a general linear model.
ScaleFactorZeroException
The computations cannot continue because a scale factor is zero.
SelectionRegression
Selects the best multiple linear regression models.
SelectionRegression..::.SummaryStatistics
SummaryStatistics contains statistics related to the regression coefficients.
SignTest
Performs a sign test.
SingularException
Covariance matrix is singular.
SingularTriangularMatrixException
Triangular matrix is singular.
Sort
A collection of sorting functions.
StepwiseRegression
Builds multiple linear regression models using forward selection, backward selection, or stepwise selection.
StepwiseRegression..::.CoefficientTTestsValue
CoefficientTTestsValue contains statistics related to the student-t test, for each regression coefficient.
Summary
Computes basic univariate statistics.
SumOfWeightsNegException
The sum of the weights have become negative.
TableMultiWay
Tallies observations into a multi-way frequency table.
TableMultiWay..::.TableBalanced
Tallies the number of unique values of each variable.
TableMultiWay..::.TableUnbalanced
Tallies the frequency of each cell in x.
TableOneWay
Tallies observations into a one-way frequency table.
TableTwoWay
Tallies observations into a two-way frequency table.
TooManyCallsException
The number of calls to the function has exceeded the maximum number of iterations times the number of moving average (MA) parameters+1.
TooManyFunctionEvaluationsException
Maximum number of function evaluations exceeded.
TooManyIterationsException
Maximum number of iterations exceeded.
TooManyIterationsReTryException
The maximum number of iterations was exceeded, increase maximum iterations or try a different parameter estimation method.
TooManyJacobianEvalException
Maximum number of Jacobian evaluations exceeded.
TooManyObsDeletedException
More observations have been deleted than were originally entered (the sum of frequencies has become negative).
UserBasisRegression
Generates summary statistics using user-supplied functions in a nonlinear regression model.
VarsDeterminedException
The variables are determined by the equality constraints.
WilcoxonRankSum
Performs a Wilcoxon rank sum test.
ZeroNormException
The computations cannot continue because the Euclidean norm of the column is equal to zero.

Interfaces

InterfaceDescription
ICdfFunction
Interface for the user-supplied cumulative distribution function to be used by InverseCdf and ChiSquaredTest.
IDistribution
Public interface for the user-supplied distribution function.
IProbabilityDistribution
Public interface for a user-supplied probability distribution.
IRandomSequence
Interface implemented by generators of random or quasi-random multidimension sequences.
IRegressionBasis
Interface for user supplied function to UserBasisRegression object.
NonlinearRegression..::.IDerivative
Public interface for the user supplied function to compute the derivative for NonlinearRegression.
NonlinearRegression..::.IFunction
Public interface for the user supplied function for NonlinearRegression.
Random..::.BaseGenerator
Base pseudorandom number.

Enumerations

EnumerationDescription
ANOVA..::.ComputeOption
Compute option.
ANOVAFactorial..::.ErrorCalculation
ErrorCalculation members indicate whether interaction effects are pooled into the error or not.
ARAutoUnivariate..::.ParamEstimation
Parameter Estimation procedures.
ARMA..::.ParamEstimation
Parameter Estimation procedures.
ARMAEstimateMissing..::.MissingValueEstimation
Missing value estimation methods.
ARSeasonalFit..::.CenterMethod
Methods for centering the input time series.
AutoARIMA..::.InformationCriterion
Indicates which information criterion is used in the optimum model search.
AutoCorrelation..::.StdErr
Standard Error computation method.
CategoricalGenLinModel..::.DistributionParameterModel
Indicates the function used to model the distribution parameter.
ClusterHierarchical..::.Linkage
Specifies the type of linkage.
ClusterHierarchical..::.Transformation
Specifies the type of transformation.
Covariances..::.MatrixType
Specifies the type of matrix to be computed.
CrossCorrelation..::.StdErr
Standard Error computation method.
DiscriminantAnalysis..::.Classification
Classification method.
DiscriminantAnalysis..::.CovarianceMatrix
Covariance matrix type.
DiscriminantAnalysis..::.Discrimination
Discrimination methods.
DiscriminantAnalysis..::.PriorProbabilities
Prior probabilities type.
Dissimilarities..::.Method
Specifies the type of distance method.
Dissimilarities..::.Scaling
Specifies the type of scaling.
FactorAnalysis..::.MatrixType
Matrix type.
FactorAnalysis..::.Model
Model type.
ProportionalHazards..::.TieHandling
Tie handling options.
Ranks..::.Tie
Determines how to break a tie.
RegressorsForGLM..::.DummyType
Dummy variable types.
SelectionRegression..::.Criterion
Criterion Methods.
StepwiseRegression..::.Direction
Direction indicator.