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WLogit

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

v2.1 · Jul 17, 2023 · GPL-2

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.

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CRAN incoming feasibility

Maintainer: ‘Wencan Zhu <wencan.zhu@yahoo.com>’

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  Authors@R: person(given = "Wencan",
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                    role = c("aut", "cre"),
                    email = "wencan.zhu@yahoo.com")
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CRAN incoming feasibility

Maintainer: ‘Wencan Zhu <wencan.zhu@yahoo.com>’

No Authors@R field in DESCRIPTION.
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  Authors@R: person(given = "Wencan",
                    family = "Zhu",
                    role = c("aut", "cre"),
                    email = "wencan.zhu@yahoo.com")
as necessary.
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Check History

NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-devel-linux-x86_64-debian-clang

CRAN incoming feasibility

Maintainer: ‘Wencan Zhu <wencan.zhu@yahoo.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "Wencan",
                    family = "Zhu",
                    role = c("aut", "cre"),
                    email = "wencan.zhu@yahoo.com")
as necessary.
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Wencan Zhu <wencan.zhu@yahoo.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "Wencan",
                    family = "Zhu",
                    role = c("aut", "cre"),
                    email = "wencan.zhu@yahoo.com")
as necessary.

Dependency Network

Dependencies Reverse dependencies cvCovEst genlasso tibble MASS ggplot2 Matrix glmnet corpcor WLogit

Version History

new 2.1 Mar 9, 2026