Nothing
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
Browse package contents
Package details |
|
|---|---|
| Author | Miika Ahdesmaki [aut], Verena Zuber [aut], Sebastian Gibb [aut], Korbinian Strimmer [aut, cre] |
| Maintainer | Korbinian Strimmer <strimmerlab@gmail.com> |
| License | GPL (>= 3) |
| Version | 1.3.9 |
| URL | https://strimmerlab.github.io/software/sda/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the sda package in your browser
Any scripts or data that you put into this service are public.
