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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=calibrationband to link to this page.
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