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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 |
| 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 |
| Reference manual: | calibrationband.pdf |
| Package source: | calibrationband_0.2.1.tar.gz |
| Windows binaries: | r-devel: calibrationband_0.2.1.zip, r-release: calibrationband_0.2.1.zip, r-oldrel: calibrationband_0.2.1.zip |
| macOS binaries: | r-release (arm64): calibrationband_0.2.1.tgz, r-oldrel (arm64): calibrationband_0.2.1.tgz, r-release (x86_64): calibrationband_0.2.1.tgz, r-oldrel (x86_64): calibrationband_0.2.1.tgz |
| Old sources: | calibrationband archive |
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