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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 |
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 |
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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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.