plsRglm: Partial least squares Regression for generalized linear models

This package provides Partial least squares Regression for (weighted) 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: 0.8.3
Depends: R (≥ 2.4.0)
Imports: mvtnorm, boot, bipartite
Suggests: MASS, plsdof
Enhances: pls
Published: 2014-03-10
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/
NeedsCompilation: no
Classification/MSC: 62J12, 62J99
Citation: plsRglm citation info
Materials: NEWS
CRAN checks: plsRglm results

Downloads:

Reference manual: plsRglm.pdf
Package source: plsRglm_0.8.3.tar.gz
MacOS X binary: plsRglm_0.8.3.tgz
Windows binary: plsRglm_0.8.3.zip
Old sources: plsRglm archive

Reverse dependencies:

Reverse imports: plsRbeta, plsRcox