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: 1.3.7
Depends: R (≥ 3.0.2), entropy (≥ 1.2.1), corpcor (≥ 1.6.8), fdrtool (≥ 1.2.15)
Imports: graphics, stats, utils
Suggests: crossval (≥ 1.0.3)
Published: 2015-07-08
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_1.3.7.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): sda_1.3.7.tgz, r-release (x86_64): sda_1.3.7.tgz, r-oldrel: sda_1.3.7.tgz
Old sources: sda archive

Reverse dependencies:

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


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