Chapter 2: Regression

IMSL C Stat Library

Functions

Multivariate Linear Regression—Model Fitting

Generates regressors for a general linear model, regressors_for_glm

Fits a multivariate linear regression model, regression

Multivariate Linear Regression—Statistical Inference and Diagnostics

Produces summary statistics for a regression model, regression_summary

Computes predicted values, confidence intervals, and diagnostics, regression_prediction

Construction of a completely testable hypothesis, hypothesis_partial

Sums of cross products for a multivariate hypothesis, hypothesis_scph

Tests for the multivariate linear hypothesis, hypothesis_test

Variable Selection

All best regressions, regression_selection

Stepwise regression, regression_stepwise

Polynomial and Nonlinear Regression

Fits a polynomial regression model, poly_regression

Computes predicted values, confidence intervals, and diagnostics, poly_prediction

Fits a nonlinear regression model, nonlinear_regression

Fits a nonlinear regression model using Powell's algorithm, nonlinear_optimization

Alternatives to Least Squares Regression

LAV, Lpnorm, and LMV criteria regression, Lnorm_regression

Performs partial least squares (PLS) regression, pls_regression