CRAN/E | glmnet

glmnet

Lasso and Elastic-Net Regularized Generalized Linear Models

Installation

About

Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression, Cox model, multiple-response Gaussian, and the grouped multinomial regression; see doi:10.18637/jss.v033.i01 and doi:10.18637/jss.v039.i05. There are two new and important additions. The family argument can be a GLM family object, which opens the door to any programmed family (doi:10.18637/jss.v106.i01). This comes with a modest computational cost, so when the built-in families suffice, they should be used instead. The other novelty is the relax option, which refits each of the active sets in the path unpenalized. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the papers cited.

Citation glmnet citation info
glmnet.stanford.edu
System requirements C++17

Key Metrics

Version 4.1-8
R ≥ 3.6.0
Published 2023-08-22 332 days ago
Needs compilation? yes
License GPL-2
CRAN checks glmnet results

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Maintainer

Maintainer

Trevor Hastie

Authors

Jerome Friedman

aut

Trevor Hastie

aut / cre

Rob Tibshirani

aut

Balasubramanian Narasimhan

aut

Kenneth Tay

aut

Noah Simon

aut

Junyang Qian

ctb

James Yang

aut

Material

README
NEWS
Reference manual
Package source

In Views

MachineLearning
Survival

Vignettes

Regularized Cox Regression
An Introduction to glmnet
The family Argument for glmnet
The Relaxed Lasso

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

glmnet archive

Depends

R ≥ 3.6.0
Matrix ≥ 1.0-6

Imports

methods
utils
foreach
shape
survival
Rcpp

Suggests

knitr
lars
testthat
xfun
rmarkdown

LinkingTo

RcppEigen
Rcpp

Reverse Depends

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ipflasso
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mcen
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MetGen
mmabig
MNS
mpath
MRFcov
MTPS
MultiGlarmaVarSel
MultiVarSel
mvs
NBtsVarSel
netcox
omada
PAS
personalized
ProSGPV
prototest
qut
RLassoCox
roccv
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sharpPen
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sox
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Compositional
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Reverse Enhances

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