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: 0.2-9
Depends: Rcpp, ggplot2, Matrix
Imports: reshape2, methods, scales, grid, parallel
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, spelling, lars, elasticnet, glmnet
Published: 2022-08-25
Author: Julien Chiquet ORCID iD [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:

Reference manual: quadrupen.pdf

Downloads:

Package source: quadrupen_0.2-9.tar.gz
Windows binaries: r-devel: quadrupen_0.2-9.zip, r-release: quadrupen_0.2-9.zip, r-oldrel: quadrupen_0.2-9.zip
macOS binaries: r-release (arm64): quadrupen_0.2-9.tgz, r-oldrel (arm64): quadrupen_0.2-9.tgz, r-release (x86_64): quadrupen_0.2-9.tgz, r-oldrel (x86_64): quadrupen_0.2-9.tgz
Old sources: quadrupen archive

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