The following classes exist within the Stat assembly:
Class | Brief description | |
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. |
See also:
Stat Assembly Interfaces | Stat Assembly Enumerations | Examples