Movatterモバイル変換


[0]ホーム

URL:


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:10.1007/s11222-014-9498-5>.

Version:1.6
Imports:methods
Suggests:testthat,knitr,rmarkdown
Published:2025-05-08
DOI:10.32614/CRAN.package.gglasso
Author:Yi Yang [aut, cre] (http://www.math.mcgill.ca/yyang/), Hui Zou [aut] (http://users.stat.umn.edu/~zouxx019/), Sahir Bhatnagar [aut] (http://sahirbhatnagar.com/)
Maintainer:Yi Yang <yi.yang6 at mcgill.ca>
BugReports:https://github.com/archer-yang-lab/gglasso/issues
License:GPL-2
URL:https://github.com/archer-yang-lab/gglasso
NeedsCompilation:yes
Materials:README,ChangeLog
CRAN checks:gglasso results

Documentation:

Reference manual:gglasso.html ,gglasso.pdf

Downloads:

Package source: gglasso_1.6.tar.gz
Windows binaries: r-devel:gglasso_1.6.zip, r-release:gglasso_1.6.zip, r-oldrel:gglasso_1.6.zip
macOS binaries: r-release (arm64):gglasso_1.6.tgz, r-oldrel (arm64):gglasso_1.6.tgz, r-release (x86_64):gglasso_1.6.tgz, r-oldrel (x86_64):gglasso_1.6.tgz
Old sources: gglasso archive

Reverse dependencies:

Reverse depends:PIE
Reverse imports:changepoints,CompMix,FIT,higlasso,ICBioMark,MLGL,PhylogeneticEM
Reverse suggests:dfr,fdaSP,sgs,sharp,sparsegl,tidyfit

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=gglassoto link to this page.


[8]ページ先頭

©2009-2025 Movatter.jp