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.
| Version: | 1.2 |
| Depends: | R (≥ 3.0.0), nnet, MASS, mvtnorm |
| Published: | 2018-05-13 |
| Author: | Yang Li, Jun S. Liu |
| Maintainer: | Yang Li <yangli.stat at gmail.com> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | sodavis results |
| Reference manual: | sodavis.pdf |
| Package source: | sodavis_1.2.tar.gz |
| Windows binaries: | r-devel: sodavis_1.2.zip, r-release: sodavis_1.2.zip, r-oldrel: sodavis_1.2.zip |
| macOS binaries: | r-release: sodavis_1.2.tgz, r-oldrel: sodavis_1.2.tgz |
| Old sources: | sodavis archive |
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