gamlr: Gamma Lasso Regression

The gamma lasso algorithm provides regularization paths corresponding to a range of non-convex cost functions between L0 and L1 norms. As much as possible, usage for this package is analogous to that for the glmnet package (which does the same thing for penalization between L1 and L2 norms). For details see: Taddy (2015), One-Step Estimator Paths for Concave Regularization, http://arxiv.org/abs/1308.5623.

Version: 1.13-3
Depends: R (≥ 2.15), Matrix, methods, graphics, stats
Suggests: parallel
Published: 2015-08-26
Author: Matt Taddy
Maintainer: Matt Taddy <taddy at chicagobooth.edu>
License: GPL-3
URL: http://github.com/TaddyLab/gamlr, http://faculty.chicagobooth.edu/matt.taddy/index.html
NeedsCompilation: yes
Citation: gamlr citation info
Materials: README
CRAN checks: gamlr results

Downloads:

Reference manual: gamlr.pdf
Package source: gamlr_1.13-3.tar.gz
Windows binaries: r-devel: gamlr_1.13-3.zip, r-release: gamlr_1.13-3.zip, r-oldrel: gamlr_1.13-3.zip
OS X Snow Leopard binaries: r-release: gamlr_1.13-3.tgz, r-oldrel: gamlr_1.13-1.tgz
OS X Mavericks binaries: r-release: gamlr_1.13-3.tgz
Old sources: gamlr archive

Reverse dependencies:

Reverse depends: distrom, textir