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JMSLTM Numerical Library 4.0 | ||||||||
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| 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. |
| ARMA | Computes least-square estimates of parameters for an ARMA model. |
| 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. |
| 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. |
| 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 | Tallies observations into a one-way frequency table. |
| TableTwoWay | Tallies observations into a two-way frequency table. |
| UserBasisRegression | Generates summary statistics using user supplied functions in a nonlinear regression model |
| WilcoxonRankSum | Performs a Wilcoxon rank sum test. |
| Exception Summary | |
| 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. |
| ARMA.TooManyFcnEvalException | Maximum number of function evaluations exceeded. |
| ARMA.TooManyITNException | Maximum number of iterations exceeded. |
| ARMA.TooManyJacobianEvalException | Maximum number of Jacobian evaluations exceeded. |
| 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. |
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JMSLTM Numerical Library 4.0 | ||||||||
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