Package: trinROC 0.7
Reinhard Furrer
trinROC: Statistical Tests for Assessing Trinormal ROC Data
Several statistical test functions as well as a function for exploratory data analysis to investigate classifiers allocating individuals to one of three disjoint and ordered classes. In a single classifier assessment the discriminatory power is compared to classification by chance. In a comparison of two classifiers the null hypothesis corresponds to equal discriminatory power of the two classifiers. See also "ROC Analysis for Classification and Prediction in Practice" by Nakas, Bantis and Gatsonis (2023), ISBN 9781482233704.
Authors:
trinROC_0.7.tar.gz
trinROC_0.7.tar.gz(r-4.5-noble)trinROC_0.7.tar.gz(r-4.4-noble)
trinROC_0.7.tgz(r-4.4-emscripten)trinROC_0.7.tgz(r-4.3-emscripten)
trinROC.pdf |trinROC.html✨
trinROC/json (API)
NEWS
| # Install 'trinROC' in R: |
| install.packages('trinROC', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Pkgdown site:https://www.math.uzh.ch
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 months agofrom:da71b33879. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 04 2024 |
| R-4.5-linux | OK | Dec 04 2024 |
Exports:boot.testboxcoxROCemp.vusfindmuroc.edaroc3.testrocsurf.emprocsurf.trintrinROC.testtrinVUS.test
Dependencies:base64encbslibcachemclicolorspacedigestevaluatefansifarverfastmapfontawesomefsggplot2gluegridExtragtablehighrhtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmepillarpkgconfigR6rappdirsRColorBrewerrglrlangrmarkdownsassscalestibbletinytexutf8vctrsviridisLitewithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| trinROC: Statistical Tests for Assessing Trinormal ROC Data | trinROC-package trinROC |
| Bootstrap test for three-class ROC data | boot.test |
| Box-Cox transformation on three-class ROC data | boxcoxROC |
| Synthetic data set to investigate three-class ROC data. | cancer |
| Empirical VUS calculation | emp.vus |
| Determine equidistant means of trinormal ROC data simulation | findmu |
| Synthetic small data set to investigate three-class ROC data. | krebs |
| Exploratory data analysis for a three-class ROC marker | roc.eda |
| Statistical test function for computing multiple tests on three-class ROC data | roc3.test |
| Empirical ROC surface plot | rocsurf.emp |
| Trinormal ROC surface plot | rocsurf.trin |
| Trinormal based ROC test | trinROC.test |
| Trinormal VUS test | trinVUS.test |