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 | 
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