plsRcox: Partial least squares Regression for Cox models and related techniques

This packages provides Partial least squares Regression and various techniques for fitting Cox models in high dimensionnal settings. It allows for Kfold crossvalidation of such models using various criteria, missing data in the eXplanatory variables. Bootstrap confidence intervals constructions are also available.

Version: 0.7.6
Depends: R (≥ 2.4.0)
Imports: boot, plsRglm, lars, survival, pls, spls, kernlab
Suggests: glcoxph, survivalROC, plsRglm, lars, survival, pls, spls, kernlab, plsRcox, plsdof
Published: 2012-11-12
Author: Frederic Bertrand, Myriam Maumy-Bertrand, Nicolas Meyer.
Maintainer: Frederic Bertrand <frederic.bertrand at math.unistra.fr>
License: GPL-3 (see file LICENCE)
URL: http://www-irma.u-strasbg.fr/~fbertran/
NeedsCompilation: no
Classification/MSC: 62N01, 62N02, 62N03, 62N99
Citation: plsRcox citation info
In views: Survival
CRAN checks: plsRcox results

Downloads:

Package source: plsRcox_0.7.6.tar.gz
MacOS X binary: plsRcox_0.7.6.tgz
Windows binary: plsRcox_0.7.6.zip
Reference manual: plsRcox.pdf
News/ChangeLog:NEWS
Old sources: plsRcox archive

Reverse dependencies:

Reverse suggests: plsRcox