Scales or unscales continuous data prior to its use in neural network training, testing, or forecasting.

Estimates the optimum seasonality parameters for a time series using an autoregressive model, AR(p), to represent the time series.

Indicates a condition has occurred in a user-supplied function necessitating a return to the calling function.

Performs the Shapiro-Wilk test for normality.

Performs a sign test.

Computes basic univariate statistics.

Sorts observations by specified keys, with option to tally cases into a multi-way frequency table.

Analyzes a wide variety of split-plot experiments with fixed, mixed or random factors.

Analyzes data from split-split-plot experiments.

Analyzes data from strip-plot experiments.

Analyzes data from strip-split-plot experiments.

Trains a Support Vector Machines classifier

Classifies patterns using a previously trained Support Vector Machines classifier

Estimates using various parametric models.

Analyzes survival data using a generalized linear model.

Frees memory allocated for a Support Vector Machines classifier