Stat Assembly > Stat Assembly Classes

Stat Assembly Classes

The following classes exist within the Stat assembly:

	Class	Brief description
	QRegStatistics	The QRegStatistics class determines quantile regression characteristics.
	Sm2SLS	The Sm2SLS class implements the instrumental variables method to estimate linear regression coefficients.
	SmARCHTest	The SmARCHTest class is used to work with parameters of the ARCH test for heteroscedasticity.
	SmAssociationRules	The SmAssociationRules class is used for data mining using the Association Analysis method.
	SmAugmentDickeyFullerTest	The SmAugmentDickeyFullerTest class is used to work with parameters of the Dickey-Fuller augmented test.
	SmAutoCorrelation	The SmAutoCorrelation class implements algorithm of the autocorrelation analysis.
	SmAutoRegress	The SmAutoRegress class implements autoregression algorithm.
	SmBackPropagation	The SmBackPropagation class is used for data mining using the Backpropagation Network method.
	SmBandpassFilter	The SmBandpassFilter class implements the Baxter-King algorithm.
	SmBetaDistribution	The SmBetaDistribution class enables the user to generate a sample of pseudo-random numbers from beta distribution with selected parameters.
	SmBinaryModel	The SmBinaryModel class implements the binary regression algorithm.
	SmBinning	The SmBinning class is used to work with the Binning procedure.
	SmBinomialDistribution	The SmBinomialDistribution class enables the user to generate a sample of pseudo-random numbers from discrete binomial distribution with selected parameters.
	SmBoxConstrainedOptimization	The SmBoxConstrainedOptimization class is used to work with optimization parameters of random type function.
	SmBreuschPaganGodfreyTest	The SmBreuschPaganGodfreyTest class is used to work with parameters of the Breusch-Pagan-Godfrey test for heteroscedasticity.
	SmBreuschPaganTest	The SmBreuschPaganTest class is used to work with parameters of the Breusch-Pagan test.
	ISmCART	The SmCART class is used to cope with classification tasks using binary tree building.
	SmCauchyDistribution	The SmCauchyDistribution class enables the user to generate a sample of pseudo-random numbers from the Cauchy distribution with selected location parameter (median) and scale parameter.
	SmCensoredTruncatedRegression	The SmCensoredTruncatedRegression class is used to estimate linear regression with truncated or censored data.
	SmCensus1	The SmCensus1 class implements the Census I method that decomposes a source series into a seasonal, trend-cycle and irregular components.
	SmCensus2	The SmCensus2 class implements the X11 method which is an improved version of the seasonal decomposition and adjustment method called Census I.
	SmChi2Distribution	The SmChi2Distribution class enables the user to generate a sample of pseudo-random numbers from χ2 (chi-square) distribution with selected number of degrees of freedom.
	SmChowTest	The SmChowTest class implements algorithm of the Chow test for the presence of structural changes.
	SmCointegratingRegression	The SmCointegratingRegression class is used to work with cointegration regression.
	SmCointegrationEq	The SmCointegrationEq class implements algorithm of the error correction method.
	SmCurveEstimation	The SmCurveEstimation class implements algorithm of dependence form selection.
	SmDecisionTree	The SmDecisionTree class is used to substitute missing data in series values using a decision tree.
	SmDerivative	The SmDerivative class is designed to calculate derivatives.
	SmDickeyFullerGLSTest	The SmDickeyFullerGLSTest class is used to work with parameters of the Dickey-Fuller generalized test.
	SmDiscriminantAnalysis	The SmDiscriminantAnalysis class is used for data mining using the Discriminatory Analysis method.
	SmElliotRothenbergStockTest	The SmElliotRothenbergStockTest class is used to work with parameters of the Elliot-Rothenberg-Stock test.
	SmEngleGrangerTest	The SmEngleGrangerTest class is used to work with parameters of the Engle-Granger test.
	SmErrorCorrectionModel	The SmErrorCorrectionModel class implements algorithm of error correction model (ECM) calculation.
	SmExponentialDistribution	The SmExponentialDistribution class enables the user to generate a sample of pseudo-random numbers from exponential distribution with selected expected value.
	SmExponentialSmoothing	The SmExponentialSmoothing class implements exponential smoothing algorithm.
	SmFillGapsProcedure	The SmFillGapsProcedure class implements algorithm of missing data treatment in data series.
	SmFisherDistribution	The SmFisherDistribution class enables the user to generate a sample of pseudo-random numbers from the Fisher distribution with two selected degrees of freedom.
	SmFisherTest	The SmFisherTest class implements the Fisher test algorithm.
	SmGammaDistribution	The SmGammaDistribution class enables the user to generate a sample of pseudo-random numbers from gamma distribution with selected shape and scale parameters.
	SmGARCH	The SmGARCH class implements algorithm of the generalized autoregressive conditionally heteroscedastic model (GARCH model).
	SmGeneralizedExtremeValueDistribution	The SmGeneralizedExtremeValueDistribution class estimates parameters of distribution of extreme values using the method of maximum likelihood.
	SmGeneralizedParetoDistribution	The SmGeneralizedParetoDistribution class estimates parameters of the generalized Pareto distribution using the method of maximum likelihood.
	SmGeometricExtrapolation	The SmGeometricExtrapolation class implements algorithm of geometric extrapolation.
	SmGradientBoostedTree	The SmGradientBoostedTree class is used to set up parameters of gradient boosting calculation.
	SmGrangerTest	The SmGrangerTest class implements the Granger test algorithm.
	SmGreyForecast	The SmGreyForecast class implements Grey forecast algorithm.
	SmHierarchicalClusterAnalysis	The SmHierarchicalClusterAnalysis class implements algorithm of hierarchical cluster analysis.
	SmHighlightExceptions	The SmHighlightExceptions class is used for data mining using the Exception Search method.
	SmHodrickPrescottFilter	The SmHodrickPrescottFilter class implements algorithm of the Hodrick-Prescott filter.
	SmHyperGeometricDistribution	The SmHyperGeometricDistribution class enables user to generate (based on selected parameters) a sample of pseudo-random numbers from discrete hypergeometric distribution of the number of "successes" in a sample from a finite population that contains "successful elements" ("successes").
	SmJohansenTest	The SmJohansenTest class implements the Johansen test algorithm.
	SmKmeansClusterAnalysis	The SmKmeansClusterAnalysis class implements algorithm for clustering using the k-means method.
	SmKolmogorovSmirnovTest	The SmKolmogorovSmirnovTest class implements algorithm of the Kolmogorov-Smirnov test.
	SmKwiatkowskiPhillipsSchmidtShinTest	The ISmKwiatkowskiPhillipsSchmidtShinTest interface is used to work with parameters of the Kwiatkowski-Phillips-Schmidt-Shin test.
	SmLIML	The SmLIML class is used to work with the maximum likelihood method with limited information and K-class estimation method.
	SmLinearEquations	The SmLinearEquations class implements algorithm of solving linear equation system.
	SmLinearProgramming	The SmLinearProgramming class implements linear programming algorithm (the Simplex method).
	SmLinearRegress	The SmLinearRegress class implements algorithm of the linear regression method.
	SmLogisticDistribution	The SmLogisticDistribution class enables the user to generate a sample of pseudo-random numbers from logistic distribution with selected location parameter (median) and scale parameter.
	SmLogisticRegression	The SmLogisticRegression class is used for data mining using the Logistic Regression method.
	SmLogNormalDistribution	The SmLogNormalDistribution class enables the user to generate a sample of pseudo-random numbers from lognormal distribution with selected expected value and variance.
	SmLongRunCovariance	The SmLongRunCovariance class is used to work with long-run covariance.
	SmLPSolveManager	The SmLPSolveManager class implements the object that is used to set the path to LPSolve solver installed and integrated with Foresight Analytics Platform.
	SmLRXFilter	The SmLRXFilter class implements algorithm of LRX filter.
	SmMarkovSwitchingGARCH	The SmMarkovSwitchingGARCH class is used to work with MS-GARCH model (Markov switching GARCH) with one variable parameter: average variance value.
	SmMedianSmoothing	The SmMedianSmoothing class implements algorithm of median smoothing.
	SmMultiNormalDistribution	The SmMultiNormalDistribution class enables the user to generate a sample of pseudo-random numbers from multivariate normal distribution.
	SmNaiveBayes	The SmNaiveBayes class is used to detect key influencers using the naive Bayes classifier.
	SmNgPerronTest	The ISmNgPerronTest class is used to work with parameters of the Ng-Perron test.
	SmNonLinearEquations	The SmNonLinearEquations class implements algorithm of non-linear equation system.
	SmNonLinearLeastSquare	The SmNonLinearLeastSquare class implements algorithm of the non-linear least squares method.
	SmNonLinearOptimization	The SmNonLinearOptimization class implements algorithm of optimization for an arbitrary function under non-linear constraints.
	SmNormalDistribution	The SmNormalDistribution class enables the user to generate vector of pseudo-random numbers based on normal distribution with selected average of distribution (expected value) and variance.
	SmOmittedVariablesTest	The SmOmittedVariablesTest class implements algorithm of omitted variables test.
	SmPairCorrelation	The SmPairCorrelation class implements algorithm for calculating paired correlation coefficients.
	SmParetoDistribution	The SmParetoDistribution class implements algorithm of the Pareto distribution.
	SmPartialCorrelation	The SmPartialCorrelation class implements algorithm for calculating partial coefficients of correlation.
	SmPhillipsOuliarisTest	The SmPhilipsOuliarisTest class is used to work with parameters of the Phillips-Ouliaris test.
	SmPhillipsPerronTest	The SmPhilipsPerronTest class is used to work with parameters of the Phillips-Perron test.
	SmPoissonDistribution	The SmPoissonDistribution class enables the user to generate a sample of pseudo-random integer numbers from the discrete Poisson distribution with specified intensity of events.
	SmPooledModel	The SmPooledModel class implements algorithm of Panel Data Regression.
	SmPrincipalComponentAnalysis	The SmPrincipalComponentAnalysis class implements algorithm of the principal components method.
	SmQPortions	The SmQPortions class implements algorithm used to calculate median, quartiles, percentiles and deciles.
	SmQuadraticProgramming	The SmQuadraticProgramming class implements a task of Quadratic Programming.
	SmQuantileRegression	The SmQuantileRegression class implements the quantile regression method.
	SmR	The SmR class is used for integration with R.
	SmRamseyRESSETTest	The SmRamseyRESSETTest class implements algorithm of the RESET test, that is the test that finds errors in specification of linear regression model (Functional form criterion).
	SmRandomForest	The ISmRandomForest interface is used to work with the Random Forest decision tree ensemble.
	SmRedundantVariablesTest	The SmRedundantVariablesTest class implements algorithm of test for redundant variables.
	SmRManager	The SmRManager class is used to set the patch to the installed and integrated with Foresight. Analytics Platform R package.
	SmRollingRegression	The ISmRollingRegression class is used to work with parameters of moving regression.
	SmSelfOrganizingMap	The SmSelfOrganizingMap class is used for data clustering using self-organizing Kohonen maps.
	SmSerialCorrelationLMTest	The SmSerialCorrelationLMTest class implements algorithm of test for autocorrelation of linear regression model residuals.
	SmSimultaneousSystem	The SmSimultaneousSystem class implements algorithm for solving simultaneous equation system.
	SmSingularSpectrumAnalysis	The SmSingularSpectrumAnalysis class is used to perform singular spectrum analysis of time series.
	SmSlideSmoothing	TheSmSlideSmoothing class implements moving average algorithm.
	SmStudentDistribution	The SmStudentDistribution class enables the user to generate a sample of pseudo-random numbers from the Student's distribution with selected number of degrees of freedom.
	SmUniformDistribution	The SmUniformDistribution class enables the user to generate a sample of pseudo-random numbers from continuous uniform distribution at the range [a, b].
	SmUnivariateSpectrumAnalysis	The SmUnivariateSpectrumAnalysis class implements spectral analysis algorithm.
	SmVarianceAnalysis	The SmVarianceAnalysis class implements variance analysis algorithm.
	SmVectorAutoRegress	The SmVectorAutoRegress class implements algorithm for vector autoregression calculation or for impulse response function calculation.
	SmWeibullDistribution	The SmWeibullDistribution class enables the user to generate a sample of pseudo-random numbers from the two-parameter Weibull distribution with selected shape and scale parameters.
	SmWhiteHeteroskedasticityTest	The SmWhiteHeteroskedasticityTest class implements algorithm of the White test for heteroskedasticity of linear regression model residuals.
	Smx12arima	The ISmx12arima class is used to work with the X12 method of seasonal adjustments.
	Statistics	The Statistics class implements algorithm of statistical functions.