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.

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AuthorMiika Ahdesmaki, Verena Zuber, Sebastian Gibb, and Korbinian Strimmer
Date of publication2015-07-08 16:28:41
MaintainerKorbinian Strimmer <>
LicenseGPL (>= 3)

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