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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 |
Documentation:
Downloads:
Linking:
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https://CRAN.R-project.org/package=trinROC
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.