Package: sda 1.3.8
Korbinian Strimmer
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.
Authors:
sda_1.3.8.tar.gz
sda_1.3.8.tar.gz(r-4.5-noble)sda_1.3.8.tar.gz(r-4.4-noble)
sda_1.3.8.tgz(r-4.4-emscripten)sda_1.3.8.tgz(r-4.3-emscripten)
sda.pdf |sda.html✨
sda/json (API)
NEWS
| # Install 'sda' in R: |
| install.packages('sda', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/strimmerlab/software/issues
Last updated 3 years agofrom:44362f36d9. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 12 2024 |
| R-4.5-linux | NOTE | Dec 12 2024 |
Exports:catscorecentroidsplot.sda.rankingpredict.sdasdasda.ranking
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| The sda Package | sda-package |
| Estimate CAT Scores and t-Scores | catscore |
| Group Centroids and (Pooled) Variances | centroids |
| Childhood Cancer Study of Khan et al. (2001) | khan2001 |
| Shrinkage Discriminant Analysis 3: Prediction Step | predict.sda |
| Shrinkage Discriminant Analysis 2: Training Step | sda |
| Shrinkage Discriminant Analysis 1: Predictor Ranking | plot.sda.ranking sda.ranking |
| Prostate Cancer Study of Singh et al. (2002) | singh2002 |