Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper linked to via the URL below.
| Version: | 2.0-5 |
| Depends: | Matrix (≥ 1.0-6), utils, foreach |
| Imports: | methods |
| Suggests: | survival, knitr, lars |
| Published: | 2016-03-17 |
| Author: | Jerome Friedman, Trevor Hastie, Noah Simon, Rob Tibshirani |
| Maintainer: | Trevor Hastie <hastie at stanford.edu> |
| BugReports: | NA |
| License: | GPL-2 |
| URL: | http://www.jstatsoft.org/v33/i01/. |
| NeedsCompilation: | yes |
| Citation: | glmnet citation info |
| Materials: | ChangeLog |
| In views: | MachineLearning |
| CRAN checks: | glmnet results |
| Reference manual: | glmnet.pdf |
| Vignettes: |
An Introduction to Glmnet Fitting the Penalized Cox Model |
| Package source: | glmnet_2.0-5.tar.gz |
| Windows binaries: | r-devel: glmnet_2.0-5.zip, r-release: glmnet_2.0-5.zip, r-oldrel: glmnet_2.0-5.zip |
| OS X Mavericks binaries: | r-release: glmnet_2.0-5.tgz, r-oldrel: glmnet_2.0-5.tgz |
| Old sources: | glmnet archive |