CRAN/E | WLogit

WLogit

Variable Selection in High-Dimensional Logistic Regression Models using a Whitening Approach

Installation

About

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.

Key Metrics

Version 2.1
R ≥ 3.5.0
Published 2023-07-17 290 days ago
Needs compilation? no
License GPL-2
CRAN checks WLogit results

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Maintainer

Maintainer

Wencan Zhu

wencan.zhu@yahoo.com

Authors

Wencan Zhu

Material

Reference manual
Package source

Vignettes

WLogit package

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

WLogit archive

Depends

R ≥ 3.5.0

Imports

cvCovEst
genlasso
tibble
MASS
ggplot2
Matrix
glmnet
corpcor

Suggests

knitr