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 fitting technique with 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.

Sensitivity Analysis

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.

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.
FittingTest_TwoSamplesKolmogorov(sample1, …) Perform a Kolmogorov goodness-of-fit test on two samples.
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_DrawClouds(*args) Draw clouds from samples.
VisualTest_DrawCobWeb(inputSample, …[, …]) Draw a Cobweb plot.
VisualTest_DrawEmpiricalCDF(*args) Draw an empirical CDF.
VisualTest_DrawHenryLine(*args) Draw an Henry plot.
VisualTest_DrawHistogram(*args) Draw an histogram.
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.

Hypothesis tests

HypothesisTest_Smirnov(firstSample, secondSample) Test whether two samples follows the same distribution.
HypothesisTest_ChiSquared(firstSample, …) Test whether two discrete samples are independent.
HypothesisTest_FullPearson(firstSample, …) Test whether two discrete samples are independent.
HypothesisTest_FullRegression(firstSample, …) Test whether two discrete samples are not linear.
HypothesisTest_FullSpearman(firstSample, …) Test whether two discrete samples are not monotonous.
HypothesisTest_PartialPearson(firstSample, …) Test whether two discrete samples are independent.
HypothesisTest_PartialRegression(…[, level]) Test whether two discrete samples are independent.
HypothesisTest_PartialSpearman(firstSample, …) Test whether two discrete samples are not monotonous.
HypothesisTest_Pearson(firstSample, secondSample) Test whether two discrete samples are independent.
HypothesisTest_Spearman(firstSample, …[, …]) Test whether two discrete samples are not monotonous.

Linear model tests

LinearModelTest_LinearModelAdjustedRSquared(*args) Test the quality of the linear regression model Test.
LinearModelTest_LinearModelFisher(*args) Test the nullity of the linear regression model coefficients.
LinearModelTest_LinearModelRSquared(*args) Test the quality of the linear regression model based on the R^2 indicator.
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.

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.

Linear models

LinearModel(*args) The linear model class is created through the method build of a LinearModelFactory.
LinearModelFactory(*args) Class used to create a linear model from numerical samples.