<p>It contains an example of a design matrix 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

X function

<p>The format is:
 num [1:50, 1:200] 0.855 1.32 1.018 -0.489 0.234 ...</p>

X: Example of a design matrix of a linear model

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Examples