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 |
| 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 El Capitan binaries: | r-release: gamlr_1.13-3.tgz |
| OS X Mavericks binaries: | r-oldrel: gamlr_1.13-3.tgz |
| Old sources: | gamlr archive |
| Reverse depends: | distrom, textir |
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