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) <doi:10.48550/arXiv.1210.2077>. Also provides a few methods for model selection purpose (cross-validation, stability selection).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2-13 |
rolling linux/jammy R-4.5 | quadrupen_0.2-13.tar.gz |
495.4 KiB |
0.2-13 |
rolling linux/noble R-4.5 | quadrupen_0.2-13.tar.gz |
505.0 KiB |
0.2-13 |
rolling source/ R- | quadrupen_0.2-13.tar.gz |
62.3 KiB |
0.2-13 |
latest linux/jammy R-4.5 | quadrupen_0.2-13.tar.gz |
495.4 KiB |
0.2-13 |
latest linux/noble R-4.5 | quadrupen_0.2-13.tar.gz |
505.0 KiB |
0.2-13 |
latest source/ R- | quadrupen_0.2-13.tar.gz |
62.3 KiB |
0.2-13 |
2026-04-26 source/ R- | quadrupen_0.2-13.tar.gz |
62.3 KiB |
0.2-13 |
2026-04-23 source/ R- | quadrupen_0.2-13.tar.gz |
62.3 KiB |
0.2-13 |
2026-04-09 windows/windows R-4.5 | quadrupen_0.2-13.zip |
920.6 KiB |
0.2-12 |
2025-04-20 source/ R- | quadrupen_0.2-12.tar.gz |
62.2 KiB |