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 protected]>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.