doi:10.48550/arXiv.1210.2077>. Also provides a few methods for model selection purpose (cross-validation, stability selection).">

quadrupen: Sparsity by Worst-Case Quadratic Penalties (original) (raw)

Fits classical sparse regression models with efficient active set algorithms by solving quadratic problems as described by Grandvalet, Chiquet and Ambroise (2017) <doi:10.48550/arXiv.1210.2077>. Also provides a few methods for model selection purpose (cross-validation, stability selection).

Version: 0.2-13
Depends: Rcpp, ggplot2, Matrix
Imports: reshape2, methods, scales, grid, parallel
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, spelling, lars, elasticnet, glmnet
Published: 2025-10-09
DOI: 10.32614/CRAN.package.quadrupen
Author: Julien Chiquet ORCID iD [aut, cre]
Maintainer: Julien Chiquet <julien.chiquet at inrae.fr>
BugReports: https://github.com/jchiquet/quadrupenCRAN/issues
License: GPL (≥ 3)
URL: https://github.com/jchiquet/quadrupenCRAN
NeedsCompilation: yes
Language: en-US
Citation: quadrupen citation info
Materials: README, NEWS
CRAN checks: quadrupen results

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