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 correlation-adjusted t-scores (CAT scores). Variable selection error is controlled using false non-discovery rates or higher criticism.

Version: 1.3.5
Depends: R (≥ 2.15.1), entropy (≥ 1.2.1), corpcor (≥ 1.6.7), fdrtool (≥ 1.2.13)
Suggests: crossval
Published: 2014-11-18
Author: Miika Ahdesmaki, Verena Zuber, Sebastian Gibb, and Korbinian Strimmer
Maintainer: Korbinian Strimmer <strimmerlab at gmail.com>
License: GPL (≥ 3)
URL: http://strimmerlab.org/software/sda/
NeedsCompilation: no
Citation: NA
Materials: NA
In views: MachineLearning
CRAN checks: sda results

Downloads:

Reference manual: sda.pdf
Package source: sda_1.3.5.tar.gz
Windows binaries: r-devel: sda_1.3.5.zip, r-release: sda_1.3.5.zip, r-oldrel: sda_1.3.5.zip
OS X Snow Leopard binaries: r-release: sda_1.3.5.tgz, r-oldrel: sda_1.3.5.tgz
OS X Mavericks binaries: r-release: sda_1.3.5.tgz
Old sources: sda archive

Reverse dependencies:

Reverse depends: st
Reverse imports: FADA
Reverse suggests: crossval, fscaret, mlr