Routines for Regression

See Chapter 14, "Regression" or select a link below.

Multiple Linear Regression

IMSL_REGRESSORS—Generates regressors for a general linear model.

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

IMSL_MULTIPREDICT—Computes predicted values, confidence intervals, and diagnostics.

Variable Selection

IMSL_ALLBEST—All best regressions.

IMSL_STEPWISE—Stepwise regression.

Polynomial and Nonlinear Regression

IMSL_POLYREGRESS—Fits a polynomial regression model.

IMSL_POLYPREDICT—Computes predicted values, confidence intervals, and diagnostics.

IMSL_NONLINREGRESS—Fits a nonlinear regression model.

Multivariate Linear Regression—Statistical Inference and Diagnostics

IMSL_HYPOTH_PARTIAL—Construction of a completely testable hypothesis.

IMSL_HYPOTH_SCPH—Sums of cross products for a multivariate hypothesis.

IMSL_HYPOTH_TEST—Tests for the multivariate linear hypothesis.

Polynomial and Nonlinear Regression

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

Alternatives to Least Squares Regression

IMSL_LNORMREGRESS—LAV, Lpnorm, and LMV criteria regression.