modelskill: Assessing and Visualising the Performance of Prediction Models

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) <doi:10.1016/j.geoderma.2021.115332> and the uncertainty-validation framework of Schmidinger and Heuvelink (2023) <doi:10.1016/j.geoderma.2023.116585>.

Version:	0.1.1
Imports:	ggplot2 (≥ 3.5.0), ggrepel, viridis
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown, pkgdown
Published:	2026-09-17
DOI:	10.32614/CRAN.package.modelskill (may not be active yet)
Author:	Alexandre M.J.-C. Wadoux [aut, cre, cph]
Maintainer:	Alexandre M.J.-C. Wadoux <alexandre.wadoux at yahoo.fr>
BugReports:	https://github.com/AlexandreWadoux/modelskill/issues
License:	MIT + file LICENSE
URL:	https://github.com/AlexandreWadoux/modelskill, https://alexandrewadoux.github.io/modelskill/
NeedsCompilation:	no
Citation:	modelskill citation info
Materials:	README, NEWS
CRAN checks:	modelskill results

Documentation:

Reference manual:	modelskill.html , modelskill.pdf
Vignettes:	Prediction performance metrics (source, R code) Predictive-uncertainty evaluation (source, R code) Summary diagrams and diagnostic plots (source, R code)

Downloads:

Package source:	modelskill_0.1.1.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): modelskill_0.1.1.tgz, r-release (x86_64): modelskill_0.1.1.tgz, r-oldrel (x86_64): modelskill_0.1.1.tgz

Linking:

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