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: 1.3.2
Depends: R (≥ 2.15.1), entropy (≥ 1.2.0), corpcor (≥ 1.6.6), fdrtool (≥ 1.2.11)
Published: 2014-01-10
Author: Miika Ahdesmaki, Verena Zuber, Sebastian Gibb, and Korbinian Strimmer
Maintainer: Korbinian Strimmer <strimmer at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: NEWS
In views: MachineLearning
CRAN checks: sda results


Reference manual: sda.pdf
Package source: sda_1.3.2.tar.gz
MacOS X binary: sda_1.3.2.tgz
Windows binary:
Old sources: sda archive

Reverse dependencies:

Reverse depends: st
Reverse suggests: fscaret