<p>It contains an example of a response variable of a linear model.</p>

datasets

It proposes a novel variable selection approach taking into account the correlations that may exist between the predictors of the design matrix in a high-dimensional linear model. Our approach consists in rewriting the initial high-dimensional linear model to remove the correlation between the predictors and in applying the generalized Lasso criterion. For further details we refer the reader to the paper <arXiv:2007.10768> (Zhu et al., 2020).

Wencan Zhu

WLasso

Variable Selection for Highly Correlated Predictors

Celine Levy-Leduc

Nils Ternes

Y function

<p>The format is:
 num [1:50, 1] 6.027 0.656 3.305 -1.922 -4.943 ...</p>

Y: Example of a response variable of a linear model.

Description

Usage

Arguments

Format

Examples