The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

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
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/emeryyi/gglasso/issues
License: GPL-2
URL: https://github.com/emeryyi/gglasso
NeedsCompilation: yes
Materials: README ChangeLog
CRAN checks: gglasso results

Documentation:

Reference manual: gglasso.pdf
Vignettes: Introduction to gglasso

Downloads:

Package source: gglasso_1.5.1.tar.gz
Windows binaries: r-devel: gglasso_1.5.1.zip, r-release: gglasso_1.5.1.zip, r-oldrel: gglasso_1.5.1.zip
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, ecpc, FIT, higlasso, ICBioMark, MLGL, PhylogeneticEM, PRSPGx
Reverse suggests: fdaSP, sgs, sharp, sparsegl

Linking:

Please use the canonical form https://CRAN.R-project.org/package=gglasso to link to this page.

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.
Health stats visible at Monitor.