This package 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 CAT scores (correlation-adjusted t-scores). Variable selection error is controlled using false non-discovery rates or higher criticism scores.
| Version: | 1.3.0 |
| Depends: | R (≥ 2.15.0), entropy (≥ 1.1.8), corpcor (≥ 1.6.5), fdrtool (≥ 1.2.10) |
| Published: | 2013-04-28 |
| Author: | Miika Ahdesmaki, Verena Zuber, Sebastian Gibb, and Korbinian Strimmer |
| Maintainer: | Korbinian Strimmer <strimmer at uni-leipzig.de> |
| License: | GPL (≥ 3) |
| URL: | http://strimmerlab.org/software/sda/ |
| NeedsCompilation: | no |
| In views: | MachineLearning |
| CRAN checks: | sda results |
| Package source: | sda_1.3.0.tar.gz |
| MacOS X binary: | sda_1.3.0.tgz |
| Windows binary: | sda_1.3.0.zip |
| Reference manual: | sda.pdf |
| News/ChangeLog: | NEWS |
| Old sources: | sda archive |
| Reverse depends: | st |
| Reverse suggests: | caret, fscaret |