# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ 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 doi: 10.32614/CRAN.package.modelskill 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) and the uncertainty-validation framework of Schmidinger and Heuvelink (2023) . 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 doi: 10.32614/CRAN.package.modelskill url: https://CRAN.R-project.org/package=modelskill repository: https://alexandrewadoux.r-universe.dev repository-code: https://github.com/AlexandreWadoux/modelskill commit: 6bcd03833b0eb95fb717f9a073247308f3be2df7 url: https://alexandrewadoux.github.io/modelskill/ date-released: '2026-09-21' contact: - family-names: Wadoux given-names: Alexandre M.J.-C. email: alexandre.wadoux@yahoo.fr orcid: https://orcid.org/0000-0001-7325-9716