MultiVarSel-package: Package

In MultiVarSel: Variable Selection in a Multivariate Linear Model

Description

MultiVarSel consists of four functions: "whitening.R", "whitening_test.R", "whitening_choice.R" and "variable_selection.R". For further information on how to use these functions, we refer the reader to the vignette of the package.

Details

This package consists of four functions: "whitening.R", "whitening_test.R", "whitening_choice.R" and "variable_selection.R". For further information on how to use these functions, we refer the reader to the vignette of the package.

Author(s)

Marie Perrot-Dockes, Celine Levy-Leduc, Julien Chiquet

Maintainer: Marie Perrot-Dockes <[e-mail]>

References

M. Perrot-Dockes et al. "A multivariate variable selection approach for analyzing LC-MS metabolomics data", arXiv:1704.00076

Examples

data("copals_camera")
Y <- scale(Y[, 1:50])
X <- model.matrix(~ group + 0)
residuals <- lm(as.matrix(Y) ~ X - 1)$residuals
S12_inv <- whitening(residuals, "AR1", pAR = 1, qMA = 0)
Frequencies <- variable_selection(
  Y = Y, X = X,
  square_root_inv_hat_Sigma = S12_inv,
  nb_repli = 10,  nb.cores = 1, parallel = FALSE
)
## Not run: 
# Parallel computing
require(doMC)
registerDoMC(cores=4)
Freqs <- variable_selection(Y,X,square_root_inv_hat_Sigma,
                    nb_repli=10,parallel=TRUE,nb.cores=4)

## End(Not run)                   

MultiVarSel documentation built on May 2, 2019, 7:58 a.m.