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stepPenal  

Stepwise Forward Variable Selection in Penalized Regression
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("stepPenal", "0.2")



Attach the package and use:
library("stepPenal")
Maintained by
Eleni Vradi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-12-23
Latest Update: 2018-08-24
Description:
Model Selection Based on Combined Penalties. This package implements a stepwise forward variable selection algorithm based on a penalized likelihood criterion that combines the L0 with L2 or L1 norms.
How to cite:
Eleni Vradi (2016). stepPenal: Stepwise Forward Variable Selection in Penalized Regression. R package version 0.2, https://cran.r-project.org/web/packages/stepPenal. Accessed 04 Jun. 2026.
Previous versions and publish date:
0.1 (2016-12-23 13:42)
Other packages that cited stepPenal R package
View stepPenal citation profile
Other R packages that stepPenal depends, imports, suggests or enhances
Complete documentation for stepPenal
Functions, R codes and Examples using the stepPenal R package
Some associated functions: SimData . StepPenal . StepPenalL2 . findROC . lassomodel . objFun . optimPenaLik . optimPenaLikL2 . penalBrier . stepaic . tuneParam . tuneParamCL2 . 
Some associated R codes: Full stepPenal package functions and examples
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