sodavis
SODA: Main and Interaction Effects Selection for Logistic Regression, Quadratic Discriminant and General Index Models
Variable and interaction selection are essential to classification in high-dimensional setting. In this package, we provide the implementation of SODA procedure, which is a forward-backward algorithm that selects both main and interaction effects under logistic regression and quadratic discriminant analysis. We also provide an extension, S-SODA, for dealing with the variable selection problem for semi-parametric models with continuous responses.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2 |
rolling linux/jammy R-4.5 | sodavis_1.2.tar.gz |
2.5 MiB |
1.2 |
rolling linux/noble R-4.5 | sodavis_1.2.tar.gz |
2.5 MiB |
1.2 |
rolling source/ R- | sodavis_1.2.tar.gz |
2.5 MiB |
1.2 |
latest linux/jammy R-4.5 | sodavis_1.2.tar.gz |
2.5 MiB |
1.2 |
latest linux/noble R-4.5 | sodavis_1.2.tar.gz |
2.5 MiB |
1.2 |
latest source/ R- | sodavis_1.2.tar.gz |
2.5 MiB |
1.2 |
2026-04-26 source/ R- | sodavis_1.2.tar.gz |
2.5 MiB |
1.2 |
2026-04-23 source/ R- | sodavis_1.2.tar.gz |
2.5 MiB |
1.2 |
2026-04-09 windows/windows R-4.5 | sodavis_1.2.zip |
2.5 MiB |
1.2 |
2025-04-20 source/ R- | sodavis_1.2.tar.gz |
2.5 MiB |