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

Install the latest version of this package by entering the following in R:
install.packages("glmnet")
AuthorJerome Friedman, Trevor Hastie, Noah Simon, Rob Tibshirani
Date of publication2016-03-17 14:00:48
MaintainerTrevor Hastie <hastie@stanford.edu>
LicenseGPL-2
Version2.0-5
http://www.jstatsoft.org/v33/i01/.

View on CRAN

Functions

auc Man page
auc.mat Man page
beta_CVX Man page
coef.cv.glmnet Man page
coef.glmnet Man page
coefnorm Man page
coxnet Man page
coxnet.deviance Man page
cvcompute Man page
cv.coxnet Man page
cv.elnet Man page
cv.fishnet Man page
cv.glmnet Man page
cv.lognet Man page
cv.mrelnet Man page
cv.multnet Man page
deviance.glmnet Man page
elnet Man page
error.bars Man page
fishnet Man page
fix.lam Man page
getcoef Man page
getcoef.multinomial Man page
getmin Man page
glmnet Man page
glmnet.control Man page
glmnet-package Man page
glmnet_softmax Man page
jerr Man page
jerr.coxnet Man page
jerr.elnet Man page
jerr.fishnet Man page
jerr.lognet Man page
jerr.mrelnet Man page
lambda.interp Man page
lognet Man page
mrelnet Man page
na.mean Man page
nonzeroCoef Man page
plotCoef Man page
plot.cv.glmnet Man page
plot.glmnet Man page
plot.mrelnet Man page
plot.multnet Man page
predict.coxnet Man page
predict.cv.glmnet Man page
predict.elnet Man page
predict.fishnet Man page
predict.glmnet Man page
predict.lognet Man page
predict.mrelnet Man page
predict.multnet Man page
print.glmnet Man page
response.coxnet Man page
rmult Man page
x Man page
y Man page
zeromat Man page

Files

inst
inst/CITATION
inst/doc
inst/doc/glmnet_beta.html
inst/doc/Coxnet.pdf
inst/doc/Coxnet.rnw
inst/doc/Coxnet.R inst/doc/glmnet_beta.R
inst/doc/glmnet_beta.Rmd
inst/mortran
inst/mortran/glmnet5.m
configure.in
src
src/Makevars.in
src/glmnet5.f90
src/Makevars.win
NAMESPACE
data
data/CoxExample.RData
data/BinomialExample.RData
data/MultiGaussianExample.RData
data/MultinomialExample.RData
data/PoissonExample.RData
data/CVXResults.RData
data/SparseExample.RData
data/QuickStartExample.RData
R
R/error.bars.R R/jerr.fishnet.R R/plot.mrelnet.R R/coxnet.R R/cvcompute.R R/predict.lognet.R R/fix.lam.R R/na.mean.R R/plot.glmnet.R R/rmult.R R/fishnet.R R/onAttach.R R/cv.fishnet.R R/cv.glmnet.R R/predict.multnet.R R/jerr.lognet.R R/response.coxnet.R R/glmnet.R R/glmnet_softmax.R R/deviance.glmnet.R R/coxnet.deviance.R R/coef.cv.glmnet.R R/mrelnet.R R/cv.mrelnet.R R/plot.multnet.R R/coef.glmnet.R R/plotCoef.R R/jerr.elnet.R R/cv.coxnet.R R/glmnet.control.R R/predict.fishnet.R R/predict.coxnet.R R/cv.lognet.R R/getcoef.multinomial.R R/lambda.interp.R R/zeromat.R R/predict.elnet.R R/predict.mrelnet.R R/cv.multnet.R R/nonzeroCoef.R R/auc.mat.R R/jerr.coxnet.R R/predict.cv.glmnet.R R/jerr.R R/getcoef.R R/cv.elnet.R R/elnet.R R/lognet.R R/predict.glmnet.R R/jerr.mrelnet.R R/coefnorm.R R/auc.R R/plot.cv.glmnet.R R/print.glmnet.R R/getmin.R
vignettes
vignettes/VignetteExample.rdata
vignettes/Coxnet.rnw
vignettes/glmnet_beta.Rmd
MD5
build
build/vignette.rds
DESCRIPTION
configure
ChangeLog
man
man/plot.cv.glmnet.Rd man/plot.glmnet.Rd man/glmnet-internal.Rd man/predict.glmnet.Rd man/cv.glmnet.Rd man/beta_CVX.Rd man/glmnet.Rd man/glmnet.control.Rd man/print.glmnet.Rd man/deviance.glmnet.Rd man/predict.cv.glmnet.Rd man/glmnet-package.Rd
configure.win
cleanup

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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