Package: sodavis
Type: Package
Title: SODA: Main and Interaction Effects Selection for Logistic
        Regression, Quadratic Discriminant and General Index Models
Version: 1.1
Depends: R (>= 3.0.0), nnet, MASS, mvtnorm
Date: 2018-04-30
Author: Yang Li, Jun S. Liu
Maintainer: Yang Li <yangli.stat@gmail.com>
Description: 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.
License: GPL-2
NeedsCompilation: no
Packaged: 2018-05-01 02:59:02 UTC; yangli
Repository: CRAN
Date/Publication: 2018-05-01 03:43:38 UTC
