CRAN/E | penalized

penalized

L1 (Lasso and Fused Lasso) and L2 (Ridge) Penalized Estimation in GLMs and in the Cox Model

Installation

About

Fitting possibly high dimensional penalized regression models. The penalty structure can be any combination of an L1 penalty (lasso and fused lasso), an L2 penalty (ridge) and a positivity constraint on the regression coefficients. The supported regression models are linear, logistic and Poisson regression and the Cox Proportional Hazards model. Cross-validation routines allow optimization of the tuning parameters.

Citation penalized citation info

Key Metrics

Version 0.9-52
R ≥ 2.10.0
Published 2022-04-23 731 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks penalized results

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Maintainer

Maintainer

Jelle Goeman

j.j.goeman@lumc.nl

Authors

Jelle Goeman
Rosa Meijer
Nimisha Chaturvedi
Matthew Lueder

Material

README
ChangeLog
Reference manual
Package source

In Views

MachineLearning
Survival

Vignettes

Penalized user guide

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

penalized archive

Depends

R ≥ 2.10.0
survival
methods

Imports

Rcpp

Suggests

globaltest

LinkingTo

Rcpp
RcppArmadillo

Reverse Depends

DIFtree
GRridge
PACLasso
structree

Reverse Imports

DIFboost
DIFlasso
GSelection
hdnom
mispr
netZooR
pensim
scRecover
splmm

Reverse Suggests

catdata
confSAM
fscaret
globaltest
lda
mlr
MWLasso
ordinalNet
peperr
riskRegression
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