Package: glmnet
Type: Package
Title: Lasso and Elastic-Net Regularized Generalized Linear Models
Version: 2.0-2
Date: 2015-4-11
Author: Jerome Friedman, Trevor Hastie, Noah Simon, Rob Tibshirani
Maintainer: Trevor Hastie <hastie@stanford.edu>
Depends: Matrix (>= 1.0-6), utils, foreach
Suggests: survival, knitr, lars
Description: 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. 
License: GPL-2
VignetteBuilder: knitr
URL: http://www.jstatsoft.org/v33/i01/.
Packaged: 2015-04-11 10:00:57 UTC; hastie
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2015-04-12 00:56:25
Built: R 3.2.2; x86_64-pc-linux-gnu; 2015-09-15 16:35:28 UTC; unix
