Other packages > Find by keyword >

modelimportance  

Measuring Contributions of Component Models to Ensemble Forecast Accuracy
View on CRAN: Click here


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
[Scholar Profile | Author Map]
All associated links for this package
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.
Previous versions and publish date:
No previous versions
Other packages that cited modelimportance R package
View modelimportance citation profile
Other R packages that modelimportance depends, imports, suggests or enhances
Complete documentation for modelimportance
Functions, R codes and Examples using the modelimportance R package
Full modelimportance package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

gemlog  
File Conversion for "Gem Infrasound Logger"
Reads data files from the 'Gem infrasound logger' for analysis and converts to segy format (which is ...
Download / Learn more Package Citations See dependency  
magicfor  
Magic Functions to Obtain Results from for Loops
Magic functions to obtain results from for loops. ...
Download / Learn more Package Citations See dependency  
forecastHybrid  
Convenient Functions for Ensemble Time Series Forecasts
Convenient functions for ensemble forecasts in R combining approaches from the 'forecast' package. ...
Download / Learn more Package Citations See dependency  
climwin  
Climate Window Analysis
Contains functions to detect and visualise periods of climate sensitivity (climate windows) for a g ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
givitiR  
The GiViTI Calibration Test and Belt
Functions to assess the calibration of logistic regression models with the GiViTI (Gruppo Italiano p ...
Download / Learn more Package Citations See dependency  

29,080

R Packages

247,686

Dependencies

77,281

Author Associations

29,081

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA