quadrupen: Sparsity by Worst-Case Quadratic Penalties
Fits classical sparse regression models with
efficient active set algorithms by solving quadratic problems as described by
Grandvalet, Chiquet and Ambroise (2017) <arXiv:1210.2077>. Also provides a few
methods for model selection purpose (cross-validation, stability selection).
Version: |
0.2-8 |
Depends: |
Rcpp, ggplot2, Matrix |
Imports: |
reshape2, methods, scales, grid, parallel |
LinkingTo: |
Rcpp, RcppArmadillo |
Suggests: |
testthat, spelling, lars, elasticnet, glmnet |
Published: |
2020-11-18 |
Author: |
Julien Chiquet
[aut, cre] |
Maintainer: |
Julien Chiquet <julien.chiquet at inrae.fr> |
License: |
GPL (≥ 3) |
NeedsCompilation: |
yes |
Language: |
en-US |
Citation: |
quadrupen citation info |
Materials: |
README NEWS |
CRAN checks: |
quadrupen results |
Documentation:
Downloads:
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