Regression

Multiple Linear Regression

REGRESSORS

Generates regressors for a general linear model

MULTIREGRESS

Fits a multiple linear regression model and optionally produces summary statistics for a regression model

MULTIPREDICT

Computes predicted values, confidence intervals, and diagnostics

Variable Selection

ALLBEST

All best regressions

STEPWISE

Stepwise regression

Polynomial and Nonlinear Regression

POLYREGRESS

Fits a polynomial regression model

POLYPREDICT

Computes predicted values, confidence intervals, and diagnostics

NONLINREGRESS

Fits a nonlinear regression model.

Inference and Diagnostics

HYPOTH_PARTIAL

Constructs an equivalent completely testable multivariate general linear hypothesis HbU = G from a partially testable hypothesis HpbU = Gp.

HYPOTH_SCPH

Computes the matrix of sums of squares and cross products for the multivariate general linear hypothesis HbU = G given the regression fit.

HYPOTH_TEST

Performs tests for a multivariate general linear hypothesis HbU = G given the hypothesis sums of squares and cross products matrix SH.

Polynomial and Nonlinear Regression

NONLINOPT

Fit a nonlinear regression model using Powell's algorithm.

Alternatives to Least Squares Regression

LNORMREGRESS

LAV, Lpnorm, and LMV criteria regression