sda: Shrinkage Discriminant Analysis and CAT Score Variable Selection

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: 1.3.6
Depends: R (≥ 2.15.1), entropy (≥ 1.2.1), corpcor (≥ 1.6.7), fdrtool (≥ 1.2.14)
Suggests: crossval
Published: 2015-03-21
Author: Miika Ahdesmaki, Verena Zuber, Sebastian Gibb, and Korbinian Strimmer
Maintainer: Korbinian Strimmer <strimmerlab at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: NEWS
In views: MachineLearning
CRAN checks: sda results


Reference manual: sda.pdf
Package source: sda_1.3.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-oldrel: sda_1.3.6.tgz
OS X Mavericks binaries: r-release: sda_1.3.6.tgz
Old sources: sda archive

Reverse dependencies:

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