plsRglm: Partial least squares Regression for generalized linear models

This package provides Partial least squares Regression for generalized linear models and kfold crossvalidation of such models using various criteria. It allows for missing data in the eXplanatory variables. Bootstrap confidence intervals constructions are also available.

Version: 0.7.6
Depends: R (≥ 2.4.0)
Imports: mvtnorm, boot
Suggests: MASS, plsdof
Enhances: pls
Published: 2011-11-23
Author: Frederic Bertrand, Nicolas Meyer, Myriam Maumy-Bertrand.
Maintainer: Frederic Bertrand <frederic.bertrand at math.unistra.fr>
License: GPL-3
URL: http://www-irma.u-strasbg.fr/~fbertran/
Classification/MSC: 62J12, 62J99
Citation: plsRglm citation info
In views: ChemPhys, Psychometrics
CRAN checks: plsRglm results

Downloads:

Package source: plsRglm_0.7.6.tar.gz
MacOS X binary: plsRglm_0.7.6.tgz
Windows binary: plsRglm_0.7.6.zip
Reference manual: plsRglm.pdf
News/ChangeLog:NEWS
Old sources: plsRglm archive

Reverse dependencies:

Reverse depends: plsRbeta
Reverse imports: plsRcox
Reverse suggests: plsRcox
Reverse enhances: plsRbeta