Variable Selection in a Multivariate Linear Model
This is a qualitative variable indicating the type of tree each row of...
This is a dataset containing the abundance of 199 metabolites from 9 s...
Package
This is a dataset containing the abundance of 724 proteins from 9 seed...
This function allows the user to select the most relevant variables th...
This function provides an estimation of the inverse of the square root...
This function helps to choose the best whitening strategy among the fo...
This function provides the p-value of an adaptation of the Portmanteau...
This is a metabolomic dataset from 30 copals samples of trees coming f...
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>.