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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.
Getting started
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Package details |
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| Author | Miika Ahdesmaki, Verena Zuber, Sebastian Gibb, and Korbinian Strimmer |
| Maintainer | Korbinian Strimmer <strimmerlab@gmail.com> |
| License | GPL (>= 3) |
| Version | 1.3.8 |
| URL | https://strimmerlab.github.io/software/sda/ |
| Package repository | View on CRAN |
| Installation |
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