sda: Shrinkage Discriminant Analysis and CAT Score Variable Selection

This package provides an efficient framework for high-dimensional linear and diagonal discriminant analysis with variable selection. The classifier is trained using James-Stein-type shrinkage estimators and predictor variables are ranked using CAT scores (correlation-adjusted t-scores). Variable selection error is controlled using false non-discovery rates or higher criticism scores.

Version: 1.3.0
Depends: R (≥ 2.15.0), entropy (≥ 1.1.8), corpcor (≥ 1.6.5), fdrtool (≥ 1.2.10)
Published: 2013-04-28
Author: Miika Ahdesmaki, Verena Zuber, Sebastian Gibb, and Korbinian Strimmer
Maintainer: Korbinian Strimmer <strimmer at uni-leipzig.de>
License: GPL (≥ 3)
URL: http://strimmerlab.org/software/sda/
NeedsCompilation: no
In views: MachineLearning
CRAN checks: sda results

Downloads:

Package source: sda_1.3.0.tar.gz
MacOS X binary: sda_1.3.0.tgz
Windows binary: sda_1.3.0.zip
Reference manual: sda.pdf
News/ChangeLog:NEWS
Old sources: sda archive

Reverse dependencies:

Reverse depends: st
Reverse suggests: caret, fscaret