calibrationband: Calibration Bands
Package to assess the calibration of probabilistic classifiers using confidence bands for monotonic functions. Besides testing the classical goodness-of-fit null hypothesis of perfect calibration, the confidence bands calculated within that package facilitate inverted goodness-of-fit tests whose rejection allows for a sought-after conclusion of a sufficiently well-calibrated model. The package creates flexible graphical tools to perform these tests. For construction details see also Dimitriadis, Dümbgen, Henzi, Puke, Ziegel (2022) <doi:10.48550/arXiv.2203.04065>.
| Version: | 0.2.1 |
| Depends: | R (≥ 3.3) |
| Imports: | Rcpp,ggplot2,tibble,dplyr,tidyr,sp, methods, base, stats,magrittr,rlang,tidyselect |
| LinkingTo: | Rcpp |
| Published: | 2022-08-09 |
| DOI: | 10.32614/CRAN.package.calibrationband |
| Author: | Timo Dimitriadis [aut], Alexander Henzi [aut], Marius Puke [aut, cre] |
| Maintainer: | Marius Puke <marius.puke at uni-hohenheim.de> |
| License: | GPL-3 |
| URL: | https://github.com/marius-cp/calibrationband,https://marius-cp.github.io/calibrationband/ |
| NeedsCompilation: | yes |
| Citation: | calibrationband citation info |
| Materials: | README,NEWS |
| CRAN checks: | calibrationband results |
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