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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: 1.3.8
Depends: R (≥ 3.0.2), entropy (≥ 1.3.1), corpcor (≥ 1.6.10), fdrtool (≥ 1.2.17)
Imports: graphics, stats, utils
Suggests: crossval
Enhances: care
Published: 2021-11-21
DOI: 10.32614/CRAN.package.sda
Author: Miika Ahdesmaki, Verena Zuber, Sebastian Gibb, and Korbinian Strimmer
Maintainer: Korbinian Strimmer <strimmerlab at gmail.com>
License: GPL (≥ 3)
URL: https://strimmerlab.github.io/software/sda/
NeedsCompilation: no
Materials: NEWS
In views: MachineLearning
CRAN checks: sda results

Documentation:

Reference manual: sda.pdf

Downloads:

Package source: sda_1.3.8.tar.gz
Windows binaries: r-devel: sda_1.3.8.zip, r-release: sda_1.3.8.zip, r-oldrel: sda_1.3.8.zip
macOS binaries: r-release (arm64): sda_1.3.8.tgz, r-oldrel (arm64): sda_1.3.8.tgz, r-release (x86_64): sda_1.3.8.tgz, r-oldrel (x86_64): sda_1.3.8.tgz
Old sources: sda archive

Reverse dependencies:

Reverse depends: st
Reverse imports: FADA
Reverse suggests: crossval, discrim, flowml, fscaret, mlr, tidyAML
Reverse enhances: care

Linking:

Please use the canonical form https://CRAN.R-project.org/package=sda to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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