Statistica Analytical Modules
All statistical procedures are available as properties or functions via the Statistica API. In order to provide a transparent programming environment for the user, the analysis objects and their properties are arranged to correspond to the respective flow of options and dialogs, as if the respective analyses were performed interactively. To record an analysis macro, click the Options button on any analysis dialog and select Create Macro. When running analyses, all options and output choices are automatically recorded; when you select Create Macro, the complete recording of all your actions are translated into a macro that can be run to recreate the analysis.
The following are the currently available Statistica modules and the name of the respective libraries:
| Module | Library Name |
|---|---|
| Association Rules | STAASC |
| Basic Statistics | STABasicStatistics |
| Boosted Trees | STABTrees |
| Box Cox Transformations | STABoxCox |
| By Group | STAByGroup |
| Canonical Analysis | STACanonical |
| Classification Trees | STAQuickTrees |
| Cluster Analysis | STACluster |
| Correspondence Analysis | STACorrespondence |
| Cox Proportional Hazard | STACoxPH |
| Discriminant Function Analysis | STADiscriminant |
| ETL | STAETL |
| Experimental Design (DOE) | STAExperimental |
| Factor Analysis | STAFactor |
| Feature Selection and Variable Screening | STAFSL |
| General ANOVA/MANOVA | STAMANOVA |
| General CHAID Models | STAGChaid |
| General Classification and Regression Trees | STAGTrees |
| General Discriminant Analysis (GDA) Models | STAGDA |
| General Linear Models (GLM) | STAGLM |
| General Optimization | STAGOPT |
| General Partial Least Squares (PLS) Models | STAPLS |
| General Regression Models (GRM) | STAGRM |
| Generalized Additive Models | STAGAM |
| Generalized EM and k-Means Cluster Analysis | STAGCluster |
| Generalized Linear/Nonlinear (GLZ) Models | STAGLZ |
| Goodness of Fit, Classification, Prediction | STAGoodnessOfFit |
| Interactive Drill Down | STADrillDown |
| Interactive Trees | STAITrees |
| Lasso Regression | STALassoRegression |
| Link Analysis | STALink |
| Log Linear | STALogLinear |
| Machine Learning | STAMachineLearning |
| Multidimensional Scaling | STAMultidimensional |
| Multiple Regression | STARegression |
| Multivariate Adaptive Regression Splines (MARSplines) | STAMARSplines |
| Multivariate Quality Control Charts | STAMIQCVChartsLib |
| Multivariate Statistical Process Control (MSPC) | STAMSPC |
| Neural Networks | KOHONENPLOTLib |
| Nonlinear Estimation | STANonlinear |
| Nonparametrics | STANonparametrics |
| Power Analysis | STAPowerAnalysis |
| Process Analysis | STAProcessAnalysis |
| Process Optimization | STAQCMiner |
| Quality Control Charts | STAIQCVChartsLib |
| Random Forest | STARandomForest |
| Rapid Deployment of Predictive Models | STARapidDeployment |
| Reliability and Item Analysis | STAReliability |
| Rules | STATISTICA |
| Simulation and Risk Analysis | STASRA |
| Structural Equation Modeling | STASEPATH |
| Survival Analysis | STASurvival |
| Text Miner | STATextMiner |
| Time Series | STATimeSeries |
| Variance Components | STAVarianceComponents |
| Variance Estimation and Precision | STAVEPAC |