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: |
1.1.3 |
| Depends: |
glmnet, Matrix (≥ 1.2-11), parallel |
| Suggests: |
R.rsp |
| Published: |
2019-03-21 |
| 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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