Package: regRSM 0.5
Pawel Teisseyre
regRSM: Random Subspace Method (RSM) for Linear Regression
Performs Random Subspace Method (RSM) for high-dimensional linear regression to obtain variable importance measures. The final model is chosen based on validation set or Generalized Information Criterion.
Authors:
regRSM_0.5.tar.gz
regRSM_0.5.tar.gz(r-4.5-noble)regRSM_0.5.tar.gz(r-4.4-noble)
regRSM.pdf |regRSM.html✨
regRSM/json (API)
| # Install 'regRSM' in R: |
| install.packages('regRSM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 years agofrom:a68b039ee2. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 20 2024 |
| R-4.5-linux | OK | Aug 20 2024 |
Exports:ImpPlotregRSMregRSM.defaultregRSM.formularocvalidate
Dependencies:codetoolsdoParallelforeachiteratorsRmpi
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Variable importance plot from 'regRSM' object. | ImpPlot ImpPlot.regRSM |
| Plot from 'regRSM' object. | plot.regRSM |
| Predictions from a 'regRSM' object. | predict.regRSM |
| Print 'regRSM' object. | print.regRSM |
| Random Subspace Method (RSM) for linear regression. | regRSM regRSM.default regRSM.formula |
| ROC curve and AUC parameter. | roc roc.regRSM |
| Print 'regRSM' object. | summary.regRSM |
| Selects the new final model from existing 'regRSM' object. | validate validate.regRSM |