glmnet: Lasso and Elastic-Net Regularized Generalized Linear Models

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 regression. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper linked to via the URL below.

Package details

AuthorJerome Friedman [aut, cre], Trevor Hastie [aut, cre], Rob Tibshirani [aut, cre], Noah Simon [aut, ctb], Balasubramanian Narasimhan [ctb], Junyang Qian [ctb]
MaintainerTrevor Hastie <[email protected]>
Package repositoryView on CRAN
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glmnet documentation built on April 2, 2018, 5:03 p.m.