Package: WLogit
Type: Package
Title: Variable Selection in High-Dimensional Logistic Regression
        Models using a Whitening Approach
Version: 2.1
Date: 2023-07-17
Author: Wencan Zhu
Maintainer: Wencan Zhu <wencan.zhu@yahoo.com>
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.
License: GPL-2
Imports: cvCovEst, genlasso, tibble, MASS, ggplot2, Matrix, glmnet,
        corpcor
VignetteBuilder: knitr
Suggests: knitr
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2023-07-17 06:44:04 UTC; chenxi
Repository: CRAN
Date/Publication: 2023-07-17 07:10:06 UTC
Built: R 4.6.0; ; 2026-05-01 05:35:10 UTC; unix
