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 papers listed in the URL below.

Package details

AuthorJerome Friedman [aut], Trevor Hastie [aut, cre], Rob Tibshirani [aut], Balasubramanian Narasimhan [aut], Noah Simon [aut], Junyang Qian [ctb]
MaintainerTrevor Hastie <[email protected]>
LicenseGPL-2
Version3.0-1
URL https://glmnet.stanford.edu https://dx.doi.org/10.18637/jss.v033.i01 https://dx.doi.org/10.18637/jss.v039.i05
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("glmnet")

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glmnet documentation built on Nov. 15, 2019, 9:06 a.m.