Multiple Linear Regression

REGRESSORS Function—Generates regressors for a general linear model.

MULTIREGRESS Function—Fits a multiple linear regression model and optionally produces summary statistics for a regression model.

MULTIPREDICT Function—Computes predicted values, confidence intervals, and diagnostics.

Variable Selection

ALLBEST Procedure—All best regressions.

STEPWISE Procedure—Stepwise regression.

Polynomial and Nonlinear Regression

POLYREGRESS Function—Fits a polynomial regression model.

POLYPREDICT Function—Computes predicted values, confidence intervals, and diagnostics.

NONLINREGRESS Function—Fits a nonlinear regression model.

Multivariate Linear Regression—Statistical Inference and Diagnostics

HYPOTH_PARTIAL Function—Construction of a completely testable hypothesis.

HYPOTH_SCPH Function—Sums of cross products for a multivariate hypothesis.

HYPOTH_TEST Function—Tests for the multivariate linear hypothesis.

Polynomial and Nonlinear Regression

NONLINOPT Function—Fit a nonlinear regression model using Powell's algorithm.

Alternatives to Least Squares Regression

LNORMREGRESS Function—LAV, Lpnorm, and LMV criteria regression.