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glmtlp: Generalized Linear Models with Truncated Lasso Penalty

Extremely efficient procedures for fitting regularization path with l0, l1, and truncated lasso penalty for linear regression and logistic regression models. This version is a completely new version compared with our previous version, which was mainly based on R. New core algorithms are developed and are now written in C++ and highly optimized.

Version: 2.0.2
Depends: R (≥ 3.5.0)
Imports: foreach, doParallel, ggplot2
Suggests: rmarkdown, knitr, testthat (≥ 3.0.0)
Published: 2024-10-02
DOI: 10.32614/CRAN.package.glmtlp
Author: Chunlin Li ORCID iD [aut, cph], Yu Yang ORCID iD [aut, cre, cph], Chong Wu ORCID iD [aut, cph], Xiaotong Shen [ths, cph], Wei Pan [ths, cph]
Maintainer: Yu Yang <yuyang.stat at gmail.com>
License: GPL-3
URL: https://yuyangyy.com/glmtlp/
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: glmtlp results

Documentation:

Reference manual: glmtlp.pdf
Vignettes: glmtlp (source, R code)

Downloads:

Package source: glmtlp_2.0.2.tar.gz
Windows binaries: r-devel: glmtlp_2.0.2.zip, r-release: glmtlp_2.0.2.zip, r-oldrel: glmtlp_2.0.2.zip
macOS binaries: r-release (arm64): glmtlp_2.0.2.tgz, r-oldrel (arm64): glmtlp_2.0.2.tgz, r-release (x86_64): glmtlp_2.0.2.tgz, r-oldrel (x86_64): glmtlp_2.0.2.tgz
Old sources: glmtlp archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.