COP {COP}R Documentation

This package is for selecting variables for index models using correlation pursuit.

Description

This packages is for selecting variables for index models using correlation pursuit method. Correlation pursuit (COP) can be viewed as a generalization of the conventional linear stepwise regression method to semi-parametric regression models. Unlike the conventional stepwise, COP selects variables that maximize the correlation between a transformed response and a linear combination of the predictors. A sequential selection strategy is used to select variables on multiple linear combinations.

Details

Package: COP
Type: Package
Version: 1.0
Date: 2009-09-17
License:

Author(s)

Wenxuan Zhong

Maintainer: Wenxuan Zhong <wenxuan@illinois.edu>

References

Correlation Pursuit: Stepwise Variable Selection for Index Models


[Package COP version 1.0 Index]