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modelimportance
View on CRAN: Click
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Download and install modelimportance package within the R console
Install from CRAN:
install.packages("modelimportance")
Install from Github:
library("remotes")
install_github("cran/modelimportance") Install by package version:
library("remotes")
install_version("modelimportance", "0.1.0") Attach the package and use:
library("modelimportance")
Maintained by
Minsu Kim
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First Published: 2026-07-16
Latest Update: 2026-07-16
Description:
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>.
How to cite:
Minsu Kim (2026). modelimportance: Measuring Contributions of Component Models to Ensemble Forecast Accuracy. R package version 0.1.0, https://cran.r-project.org/web/packages/modelimportance. Accessed 24 Oct. 2026.
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