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modelimportance: Measuring Contributions of Component Models to Ensemble Forecast Accuracy

Provides metrics for quantifying the contribution of individual component models to the predictive accuracy of ensemble forecasts. The package implements the Leave-One-Model-Out (LOMO) and Leave-All-Subset-of-One-Model-Out (LASOMO) model importance metrics, enabling users to assess the relative importance of component models and better understand the performance of ensemble forecasting systems. Methods are described in Kim et al. (2026) <doi:10.1016/j.ijforecast.2025.12.006>.

Version: 0.1.0
Depends: R (≥ 4.1.0)
Imports: hubUtils (≥ 0.4.0), dplyr (≥ 1.1.4), hubEvals (≥ 0.3.0), hubEnsembles (≥ 0.1.9), methods (≥ 4.4.3), purrr (≥ 1.0.4), furrr (≥ 0.3.1), future (≥ 1.49.0), checkmate (≥ 2.3.3), rlang (≥ 1.1.6), stats (≥ 4.4.3)
Suggests: knitr, rmarkdown, tidyr (≥ 1.3.1), kableExtra (≥ 1.4.0), ggplot2 (≥ 4.0.1), scoringutils (≥ 2.1.2), testthat (≥ 3.0.0), progressr (≥ 0.15.1)
Published: 2026-07-16
DOI: 10.32614/CRAN.package.modelimportance (may not be active yet)
Author: Minsu Kim ORCID iD [aut, cre, cph], Li Shandross ORCID iD [aut, ctb], Zhian Kamvar ORCID iD [ctb], Nicholas Reich ORCID iD [aut], Evan Ray [aut]
Maintainer: Minsu Kim <minsu at umass.edu>
BugReports: https://github.com/mkim425/modelimportance/issues
License: MIT + file LICENSE
URL: https://github.com/mkim425/modelimportance
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: modelimportance results

Documentation:

Reference manual: modelimportance.html , modelimportance.pdf
Vignettes: Simple working examples (source, R code)
'modelimportance': Evaluating model importance within a multi-model ensemble in R (source, R code)

Downloads:

Package source: modelimportance_0.1.0.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): not available, r-release (x86_64): modelimportance_0.1.0.tgz, r-oldrel (x86_64): not available

Linking:

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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.