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) .


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1.1.2 by Marie Perrot-Dockès, 2 months ago

Browse source code at

Authors: Marie Perrot-Dockès, Céline Lévy-Leduc, Julien Chiquet

Documentation:   PDF Manual  

GPL (>= 2) license

Depends on glmnet, Matrix, parallel, tidyverse

Suggests R.rsp

See at CRAN