stepPenal: Stepwise Forward Variable Selection in Penalized Regression
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.
Version: |
0.2 |
Depends: |
R (≥ 3.5.0) |
Imports: |
glmnet, mvtnorm, pROC, dfoptim, caret, stats, base |
Published: |
2018-08-24 |
DOI: |
10.32614/CRAN.package.stepPenal |
Author: |
Eleni Vradi |
Maintainer: |
Eleni Vradi <vradi.eleni at gmail.com> |
License: |
GPL-2 |
NeedsCompilation: |
no |
CRAN checks: |
stepPenal results |
Documentation:
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