glmnet v2.0-10

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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.

Functions in glmnet

Name Description
deviance.glmnet Extract the deviance from a glmnet object
glmnet-internal Internal glmnet functions
beta_CVX Simulated data for the glmnet vignette
cv.glmnet Cross-validation for glmnet
glmnet.control internal glmnet parameters
plot.cv.glmnet plot the cross-validation curve produced by cv.glmnet
glmnet-package
glmnet fit a GLM with lasso or elasticnet regularization
plot.glmnet plot coefficients from a "glmnet" object
predict.cv.glmnet make predictions from a "cv.glmnet" object.
predict.glmnet make predictions from a "glmnet" object.
print.glmnet print a glmnet object
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Details

Type Package
Date 2017-05-05
License GPL-2
VignetteBuilder knitr
URL http://www.jstatsoft.org/v33/i01/.
NeedsCompilation yes
Packaged 2017-05-05 17:23:16 UTC; hastie
Repository CRAN
Date/Publication 2017-05-06 06:23:56 UTC

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