gamlr: Gamma Lasso Regression
Version 1.13-3

The gamma lasso algorithm provides regularization paths corresponding to a range of non-convex cost functions between L0 and L1 norms. As much as possible, usage for this package is analogous to that for the glmnet package (which does the same thing for penalization between L1 and L2 norms). For details see: Taddy (2015), One-Step Estimator Paths for Concave Regularization, http://arxiv.org/abs/1308.5623.

AuthorMatt Taddy <taddy@chicagobooth.edu>
Date of publication2015-08-26 08:39:48
MaintainerMatt Taddy <taddy@chicagobooth.edu>
LicenseGPL-3
Version1.13-3
URL http://github.com/TaddyLab/gamlr http://faculty.chicagobooth.edu/matt.taddy/index.html
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("gamlr")

Getting started

README.md

Popular man pages

AICc: Corrected AIC
cv.gamlr: Cross Validation for gamlr
gamlr: Gamma-Lasso regression
hockey: NHL hockey data
See all...

All man pages Function index File listing

Man pages

AICc: Corrected AIC
cv.gamlr: Cross Validation for gamlr
gamlr: Gamma-Lasso regression
hockey: NHL hockey data

Functions

AICc Man page Source code
checky Source code
coef.cv.gamlr Man page Source code
coef.gamlr Man page Source code
cv.gamlr Man page Source code
gamlr Man page Source code
hockey Man page
logLik.gamlr Man page Source code
plot.cv.gamlr Man page Source code
plot.gamlr Man page Source code
predict.cv.gamlr Man page Source code
predict.gamlr Man page Source code
print.cv.gamlr Source code
print.gamlr Source code
summary.cv.gamlr Source code
summary.gamlr Source code

Files

inst
inst/CITATION
src
src/Makevars
src/gui.h
src/gui.c
src/lhd.h
src/lhd.c
src/vec.c
src/vec.h
src/gamlr.c
NAMESPACE
data
data/hockey.rda
data/datalist
R
R/AICc.R
R/cv.gamlr.R
R/gamlr.R
README.md
MD5
DESCRIPTION
man
man/AICc.Rd
man/gamlr.Rd
man/hockey.Rd
man/cv.gamlr.Rd
gamlr documentation built on May 19, 2017, 8:45 a.m.

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