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.

Version: 1.0
Depends: R (≥ 3.0.0), nnet, MASS, mvtnorm
Published: 2017-05-29
Author: Yang Li, Jun S. Liu
Maintainer: Yang Li <yangli.stat at>
License: GPL-2
NeedsCompilation: no
CRAN checks: sodavis results


Reference manual: sodavis.pdf
Package source: sodavis_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: sodavis_1.0.tgz
OS X Mavericks binaries: r-oldrel: sodavis_1.0.tgz
Old sources: sodavis archive


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