Package: WLogit
Type: Package
Title: Whitening Logistic Regression for Variable Selection
Version: 1.0
Date: 2022-07-01
Author: Wencan Zhu
Maintainer: Wencan Zhu <wencan.zhu@agroparistech.fr>
Description: It proposes a novel variable selection approach in classification problem that takes into account the correlations that may exist between the predictors of the design matrix in a high-dimensional logistic model. Our approach consists in rewriting the initial high-dimensional logistic 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 Zhu et al. (2022) <arXiv:2206.14850>. 
License: GPL-2
Imports: cvCovEst, genlasso, tibble, MASS, ggplot2, Matrix, glmnet,
        corpcor
VignetteBuilder: knitr
Suggests: knitr
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2022-07-02 06:05:53 UTC; mmip
Repository: CRAN
Date/Publication: 2022-07-02 12:20:02 UTC
