A package for fitting possibly high dimensional penalized regression models. The penalty structure can be any combination of an L1 penalty (lasso and fused lasso), an L2 penalty (ridge) and a positivity constraint on the regression coefficients. The supported regression models are linear, logistic and Poisson regression and the Cox Proportional Hazards model. Cross-validation routines allow optimization of the tuning parameters.
| Version: | 0.9-45 |
| Depends: | R (≥ 2.10.0), survival, methods |
| Suggests: | globaltest |
| Published: | 2014-12-19 |
| Author: | Jelle Goeman, Rosa Meijer, Nimisha Chaturvedi |
| Maintainer: | Jelle Goeman <jelle.goeman at radboudumc.nl> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | ChangeLog |
| In views: | MachineLearning, Survival |
| CRAN checks: | penalized results |
| Reference manual: | penalized.pdf |
| Vignettes: |
Penalized user guide |
| Package source: | penalized_0.9-45.tar.gz |
| Windows binaries: | r-devel: penalized_0.9-45.zip, r-release: penalized_0.9-45.zip, r-oldrel: penalized_0.9-45.zip |
| OS X Snow Leopard binaries: | r-release: penalized_0.9-45.tgz, r-oldrel: penalized_0.9-45.tgz |
| OS X Mavericks binaries: | r-release: penalized_0.9-45.tgz |
| Old sources: | penalized archive |
| Reverse depends: | DIFlasso, DIFtree, lmmlasso, multiPIM, ROC632, subtype, uplift |
| Reverse imports: | DIFboost, hdnom, pensim |
| Reverse suggests: | catdata, fscaret, Grace, lda, mlr, peperr |