Statistics on sample

Sample

Sample(*args)

Sample of real vectors.

Building distributions from samples

DistributionFactory(*args)

Base class for probability distribution factories.

DistributionFactoryResult(*args)

Results of distribution estimation.

ArcsineFactory(*args)

Arcsine factory.

BernoulliFactory(*args)

Bernoulli factory.

BetaFactory(*args)

Beta factory.

BinomialFactory(*args)

Binomial factory.

BurrFactory(*args)

Burr factory.

ChiFactory(*args)

Chi factory.

ChiSquareFactory(*args)

Chi-Square factory.

DiracFactory(*args)

Dirac factory.

DirichletFactory(*args)

Dirichlet factory.

ExponentialFactory(*args)

Exponential factory.

FisherSnedecorFactory(*args)

Fisher-Snedecor factory.

FrechetFactory(*args)

Frechet factory.

GammaFactory(*args)

Gamma factory.

GeneralizedParetoFactory(*args)

Generalized Pareto factory.

GeometricFactory(*args)

Geometric factory.

GumbelFactory(*args)

Gumbel factory.

HistogramFactory(*args)

Histogram factory.

InverseNormalFactory(*args)

Inverse Normal factory.

KernelSmoothing(*args)

Non parametric continuous distribution estimation by kernel smoothing.

LaplaceFactory(*args)

Laplace factory.

LogisticFactory(*args)

Logistic factory.

LogNormalFactory(*args)

Lognormal factory distribution.

LogUniformFactory(*args)

Log Uniform factory.

MaximumLikelihoodFactory(*args)

Maximum likelihood factory.

MeixnerDistributionFactory(*args)

Meixner Distribution factory.

MethodOfMomentsFactory(*args)

Estimation by method of moments.

MultinomialFactory(*args)

Multinomial factory.

NegativeBinomialFactory(*args)

Negative Binomial factory.

NormalFactory(*args)

Normal factory.

PoissonFactory(*args)

Poisson factory.

RayleighFactory(*args)

Rayleigh factory.

RiceFactory(*args)

Rice factory.

SkellamFactory(*args)

Skellam factory.

StudentFactory(*args)

Student factory.

TrapezoidalFactory(*args)

Trapezoidal factory.

TriangularFactory(*args)

Triangular factory.

TruncatedNormalFactory(*args)

Truncated Normal factory.

UniformFactory(*args)

Uniform factory.

UserDefinedFactory(*args)

UserDefined factory.

WeibullFactory(*args)

Weibull factory.

Building copulas from samples

AliMikhailHaqCopulaFactory(*args)

AliMikhailHaq copula factory.

BernsteinCopulaFactory(*args)

BernsteinCopula copula factory.

ClaytonCopulaFactory(*args)

Clayton Copula factory.

FarlieGumbelMorgensternCopulaFactory(*args)

Farlie Gumbel Morgenstern Copula factory.

FrankCopulaFactory(*args)

Frank Copula factory.

GumbelCopulaFactory(*args)

Gumbel Copula factory.

NormalCopulaFactory(*args)

Normal Copula factory.

Correlation analysis

CorrelationAnalysis_PearsonCorrelation(…)

Correlation evaluation based on the Pearson correlation coefficient.

CorrelationAnalysis_SpearmanCorrelation(…)

Correlation evaluation based on the Spearman correlation coefficient.

CorrelationAnalysis_PCC(inputSample, …)

Correlation evaluation based on the Partial Correlation Coefficient.

CorrelationAnalysis_PRCC(inputSample, …)

Correlation evaluation based on the Partial Rank Correlation Coefficient.

CorrelationAnalysis_SRC(inputSample, …[, …])

Correlation evaluation based on the Standard Regression Coefficient.

CorrelationAnalysis_SRRC(inputSample, …[, …])

Correlation evaluation based on the Standard Rank Regression Coefficient.

CorrelationAnalysis_SignedSRC(inputSample, …)

Correlation evaluation based on the Signed Standard Rank Regression Coefficient.

Sensitivity Analysis

Refer to Sensivity analysis using Sobol indices.

ANCOVA(*args)

ANalysis of COVAriance method (ANCOVA).

FAST(*args)

Fourier Amplitude Sensitivity Testing (FAST).

SobolIndicesAlgorithm(*args)

Sensitivity analysis.

MartinezSensitivityAlgorithm(*args)

Sensitivity analysis using Martinez method.

SaltelliSensitivityAlgorithm(*args)

Sensitivity analysis using Saltelli method.

JansenSensitivityAlgorithm(*args)

Sensitivity analysis using Jansen method.

MauntzKucherenkoSensitivityAlgorithm(*args)

Sensitivity analysis using MauntzKucherenko method.

SobolIndicesExperiment(*args)

Experiment to computeSobol’ indices.

SobolSimulationAlgorithm(*args)

Sobol indices computation using iterative sampling.

SobolSimulationResult(*args)

Sobol simulation result.

Statistical tests

TestResult(*args)

Test result data structure.

Goodness-of-fit metrics & tests

FittingTest_BIC(\*args)

Compute the Bayesian information criterion.

FittingTest_ChiSquared(\*args)

Perform a \chi^2 goodness-of-fit test for 1-d discrete distributions.

FittingTest_Kolmogorov(\*args)

Perform a Kolmogorov goodness-of-fit test for 1-d continuous distributions.

NormalityTest_AndersonDarlingNormal(sample)

Evaluate whether a sample follows a normal distribution.

NormalityTest_CramerVonMisesNormal(sample[, …])

Evaluate whether a sample follows a normal distribution.

Graphical tests

VisualTest_DrawCobWeb(inputSample, …[, …])

Draw a Cobweb plot.

VisualTest_DrawHenryLine(\*args)

Draw an Henry plot.

VisualTest_DrawKendallPlot(\*args)

Draw kendall plot.

VisualTest_DrawLinearModel(sample1, sample2, …)

Draw a linear model plot.

VisualTest_DrawLinearModelResidual(sample1, …)

Draw a linear model residual plot.

VisualTest_DrawQQplot(\*args)

Draw a QQ-plot.

VisualTest_DrawCDFplot(\*args)

Draw a CDF-plot.

Hypothesis tests

HypothesisTest_ChiSquared(firstSample, …)

Test whether two discrete samples are independent.

HypothesisTest_FullPearson(firstSample, …)

Test whether two discrete samples are independent.

HypothesisTest_FullSpearman(firstSample, …)

Test whether two samples have no rank correlation.

HypothesisTest_PartialPearson(firstSample, …)

Test whether two discrete samples are independent.

HypothesisTest_PartialSpearman(firstSample, …)

Test whether two sample have no rank correlation.

HypothesisTest_Pearson(firstSample, secondSample)

Test whether two discrete samples are independent.

HypothesisTest_Spearman(firstSample, …[, …])

Test whether two samples have no rank correlation.

HypothesisTest_TwoSamplesKolmogorov(sample1, …)

Test whether two samples follows the same distribution.

Linear model tests

LinearModelTest_LinearModelFisher(\*args)

Test the nullity of the linear regression model coefficients.

LinearModelTest_LinearModelResidualMean(\*args)

Test zero mean value of the residual of the linear regression model.

LinearModelTest_LinearModelHarrisonMcCabe(\*args)

Test the homoskedasticity of the linear regression model residuals.

LinearModelTest_LinearModelBreuschPagan(\*args)

Test the homoskedasticity of the linear regression model residuals.

LinearModelTest_LinearModelDurbinWatson(\*args)

Test the autocorrelation of the linear regression model residuals.

LinearModelTest_FullRegression(firstSample, …)

Test whether two discrete samples are not linear.

LinearModelTest_PartialRegression(…[, level])

Test whether two discrete samples are independent.

Model selection

FittingTest_BestModelBIC(\*args)

Select the best model according to the Bayesian information criterion.

FittingTest_BestModelChiSquared(\*args)

Select the best model according to the \chi^2 goodness-of-fit test.

FittingTest_BestModelKolmogorov(\*args)

Select the best model according to the Kolmogorov goodness-of-fit test.