penalized: L1 (lasso and fused lasso) and L2 (ridge) penalized estimation in GLMs and in the Cox model

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: 0.9-42
Depends: R (≥ 2.10.0), methods, survival
Imports: survival
Suggests: globaltest
Published: 2012-11-06
Author: Jelle Goeman, Rosa Meijer, Nimisha Chaturvedi
Maintainer: Jelle Goeman <j.j.goeman at lumc.nl>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.msbi.nl/goeman
NeedsCompilation: no
In views: MachineLearning, Survival
CRAN checks: penalized results

Downloads:

Reference manual: penalized.pdf
Vignettes: Penalized user guide
Package source: penalized_0.9-42.tar.gz
MacOS X binary: penalized_0.9-42.tgz
Windows binary: penalized_0.9-42.zip
Old sources: penalized archive

Reverse dependencies:

Reverse depends: DIFlasso, lmmlasso, multiPIM, ROC632, subtype, uplift
Reverse imports: pensim
Reverse suggests: catdata, fscaret, lda, mlr, peperr