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.
| Version: | 0.7 |
| Depends: | R (≥ 3.3.0) |
| Imports: | ggplot2,rgl,gridExtra |
| Suggests: | testthat,knitr,rmarkdown,MASS,reshape |
| Published: | 2024-10-04 |
| DOI: | 10.32614/CRAN.package.trinROC |
| Author: | Samuel Noll [aut], Reinhard Furrer [aut, cre], Benjamin Reiser [ctb], Christos T. Nakas [ctb], Annina Cincera [aut] |
| Maintainer: | Reinhard Furrer <reinhard.furrer at uzh.ch> |
| BugReports: | https://git.math.uzh.ch/reinhard.furrer/trinROC/-/issues |
| License: | LGPL-2.1 |
| URL: | https://www.math.uzh.ch/pages/trinROC/ |
| NeedsCompilation: | no |
| Citation: | trinROC citation info |
| Materials: | README,NEWS |
| CRAN checks: | trinROC results |
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