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gamlr  

Gamma Lasso Regression
View on CRAN: Click here


Download and install gamlr package within the R console
Install from CRAN:
install.packages("gamlr")

Install from Github:
library("remotes")
install_github("cran/gamlr")

Install by package version:
library("remotes")
install_version("gamlr", "1.13-8")



Attach the package and use:
library("gamlr")
Maintained by
Matt Taddy
[Scholar Profile | Author Map]
First Published: 2013-03-26
Latest Update: 2023-04-16
Description:
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 (2017 JCGS), 'One-Step Estimator Paths for Concave Regularization', .
How to cite:
Matt Taddy (2013). gamlr: Gamma Lasso Regression. R package version 1.13-8, https://cran.r-project.org/web/packages/gamlr. Accessed 07 May. 2025.
Previous versions and publish date:
0.1 (2013-03-26 12:16), 1.0 (2013-07-11 07:25), 1.11-1 (2013-11-04 01:04), 1.11-2 (2014-01-30 23:58), 1.11-3 (2014-04-07 07:46), 1.11 (2013-11-01 17:35), 1.12-1 (2014-10-01 07:24), 1.12 (2014-09-16 02:08), 1.13-1 (2015-04-14 07:42), 1.13-2 (2015-08-19 00:19), 1.13-3 (2015-08-26 08:39), 1.13-4 (2018-02-11 21:41), 1.13-5 (2018-05-13 20:23), 1.13-6 (2020-06-08 23:50), 1.13-7 (2021-05-07 08:30), 1.13 (2015-04-02 00:42)
Other packages that cited gamlr R package
View gamlr citation profile
Other R packages that gamlr depends, imports, suggests or enhances
Complete documentation for gamlr
Functions, R codes and Examples using the gamlr R package
Some associated functions: AICc . cv.gamlr . doubleML . gamlr . hockey . naref . 
Some associated R codes: AICc.R . cv.gamlr.R . doubleML.R . gamlr.R . naref.R .  Full gamlr package functions and examples
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