sda: Shrinkage Discriminant Analysis and CAT Score Variable Selection (original) (raw)
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: | 1.3.9 |
|---|---|
| Depends: | R (≥ 3.4.0), entropy (≥ 1.3.2), corpcor (≥ 1.6.10), fdrtool (≥ 1.2.18) |
| Imports: | graphics, stats, utils |
| Suggests: | crossval |
| Enhances: | care |
| Published: | 2025-04-08 |
| DOI: | 10.32614/CRAN.package.sda |
| Author: | Miika Ahdesmaki [aut], Verena Zuber [aut], Sebastian Gibb [aut], Korbinian Strimmer [aut, cre] |
| Maintainer: | Korbinian Strimmer |
| License: | GPL (≥ 3) |
| URL: | https://strimmerlab.github.io/software/sda/ |
| NeedsCompilation: | no |
| Materials: | |
| In views: | MachineLearning |
| CRAN checks: | sda results |
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