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MultiVarSel  

Variable Selection in a Multivariate Linear Model
View on CRAN: Click here


Download and install MultiVarSel package within the R console
Install from CRAN:
install.packages("MultiVarSel")

Install from Github:
library("remotes")
install_github("cran/MultiVarSel")

Install by package version:
library("remotes")
install_version("MultiVarSel", "1.1.3")



Attach the package and use:
library("MultiVarSel")
Maintained by
Marie Perrot-Dockès
[Scholar Profile | Author Map]
First Published: 2017-04-04
Latest Update: 2019-03-21
Description:
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-Dock
How to cite:
Marie Perrot-Dockès (2017). MultiVarSel: Variable Selection in a Multivariate Linear Model. R package version 1.1.3, https://cran.r-project.org/web/packages/MultiVarSel. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0 (2017-04-04 17:50), 1.1.2 (2018-04-13 19:05)
Other packages that cited MultiVarSel R package
View MultiVarSel citation profile
Other R packages that MultiVarSel depends, imports, suggests or enhances
Complete documentation for MultiVarSel
Functions, R codes and Examples using the MultiVarSel R package
Some associated functions: MultiVarSel-package . Y . copals_camera . group . metab . prot . variable_selection . whitening . whitening_choice . whitening_test . 
Some associated R codes: MultiVarSel-internal.R . data.R . variable_selection.R . whitening.R . whitening_choice.R . whitening_test.R .  Full MultiVarSel package functions and examples
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