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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "modelskill" in publications use:'
type: software
license: MIT
title: 'modelskill: Assessing and Visualising the Performance of Prediction Models'
version: 0.1.1
identifiers:
- type: doi
  value: 10.32614/CRAN.package.modelskill
abstract: Provides tools for evaluating continuous predictions and their associated
  predictive uncertainty from statistical, machine-learning, geostatistical, and process-based
  models. It implements complementary measures of prediction error, association, agreement,
  efficiency, uncertainty calibration, and predictive-distribution performance, together
  with Taylor, solar, target, coverage, probability integral transform, and quantile-coverage
  diagnostics. Methods include the integrated evaluation approach of Wadoux, Walvoort
  and Brus (2022) <https://doi.org/10.1016/j.geoderma.2021.115332> and the uncertainty-validation
  framework of Schmidinger and Heuvelink (2023) <https://doi.org/10.1016/j.geoderma.2023.116585>.
authors:
- family-names: Wadoux
  given-names: Alexandre M.J.-C.
  email: alexandre.wadoux@yahoo.fr
  orcid: https://orcid.org/0000-0001-7325-9716
preferred-citation:
  type: manual
  title: 'modelskill: Assessing and Visualising the Performance of Prediction Models'
  authors:
  - family-names: Wadoux
    given-names: A.M.J.-C.
  year: '2026'
  notes: R package version 0.1.1
  url: https://github.com/AlexandreWadoux/modelskill
repository: https://cran.r-universe.dev
repository-code: https://github.com/AlexandreWadoux/modelskill
commit: 0b0ab4cb51ca8e7b6be0ff226294297470773cbc
url: https://alexandrewadoux.github.io/modelskill/
date-released: '2026-09-17'
contact:
- family-names: Wadoux
  given-names: Alexandre M.J.-C.
  email: alexandre.wadoux@yahoo.fr
  orcid: https://orcid.org/0000-0001-7325-9716