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).
|Author||Wencan Zhu [aut, cre], Celine Levy-Leduc [ctb], Nils Ternes [ctb]|
|Maintainer||Wencan Zhu <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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