MultiVarSel: Variable Selection in a Multivariate Linear Model

It performs variable selection in a multivariate linear model by estimating the covariance matrix of the residuals then use it to remove the dependence that may exist among the responses and eventually performs variable selection by using the Lasso criterion. The method is described in the paper Perrot-Dockès et al. (2017) <arXiv:1704.00076>.

Version: 1.1.2
Depends: glmnet, Matrix (≥ 1.2-11), parallel, tidyverse
Suggests: R.rsp
Published: 2018-04-13
Author: Marie Perrot-Dockès, Céline Lévy-Leduc, Julien Chiquet
Maintainer: Marie Perrot-Dockès <marie.perrocks at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: MultiVarSel results

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Reference manual: MultiVarSel.pdf
Vignettes: MultiVarSel
Package source: MultiVarSel_1.1.2.tar.gz
Windows binaries: r-devel: MultiVarSel_1.1.2.zip, r-release: MultiVarSel_1.1.2.zip, r-oldrel: MultiVarSel_1.1.2.zip
OS X binaries: r-release: MultiVarSel_1.1.2.tgz, r-oldrel: MultiVarSel_1.1.2.tgz
Old sources: MultiVarSel archive

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