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.
|Author||Miika Ahdesmaki, Verena Zuber, Sebastian Gibb, and Korbinian Strimmer|
|Date of publication||2015-07-08 16:28:41|
|Maintainer||Korbinian Strimmer <email@example.com>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
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