gglasso: Group Lasso Penalized Learning Using a Unified BMD Algorithm

A unified algorithm, blockwise-majorization-descent (BMD), for efficiently computing the solution paths of the group-lasso penalized least squares, logistic regression, Huberized SVM and squared SVM. The package is an implementation of Yang, Y. and Zou, H. (2015) DOI: <doi:10.1007/s11222-014-9498-5>.

Version: 1.5.1
Imports: methods
Suggests: testthat, knitr, rmarkdown
Published: 2024-03-24
DOI: 10.32614/CRAN.package.gglasso
Author: Yi Yang [aut, cre] (, Hui Zou [aut] (, Sahir Bhatnagar [aut] (
Maintainer: Yi Yang <yi.yang6 at>
License: GPL-2
NeedsCompilation: yes
Materials: README ChangeLog
CRAN checks: gglasso results


Reference manual: gglasso.pdf
Vignettes: Introduction to gglasso


Package source: gglasso_1.5.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): gglasso_1.5.1.tgz, r-oldrel (arm64): gglasso_1.5.1.tgz, r-release (x86_64): gglasso_1.5.1.tgz, r-oldrel (x86_64): gglasso_1.5.1.tgz
Old sources: gglasso archive

Reverse dependencies:

Reverse imports: changepoints, CompMix, ecpc, FIT, higlasso, ICBioMark, MLGL, PhylogeneticEM, PRSPGx
Reverse suggests: fdaSP, sgs, sharp, sparsegl


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