Abstract | 1. Introduction | 2. Data | 2.1 Dependencies and related software | 2.2 Model output format | 2.3 Forecast data representation | 2.4 Oracle output data | 3. Method description and algorithms | 3.1 Comparison of weighting schemes in LASOMO | 4. Evaluating models with the model_importance() function | model_importance( ) | 5. S3 class and methods | 5.1 Print method | 5.2 Summary method | 5.3 Aggregate method | 6. Examples | 6.1 Example data | Evaluation using LOMO algorithm | Evaluation using LASOMO algorithm | 7. Computational complexity | 8. Implementation and availability | Summary and discussion | Acknowledgements | Appendix | Weights for subsets in LASOMO | References
Package: modelimportance 0.1.0
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.
Authors:
modelimportance_0.1.0.tar.gz
modelimportance_0.1.0.zip(r-4.7)modelimportance_0.1.0.zip(r-4.6)modelimportance_0.1.0.zip(r-4.5)
modelimportance_0.1.0.tgz(r-4.6-any)modelimportance_0.1.0.tgz(r-4.5-any)
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modelimportance_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
modelimportance/json (API)
| # Install 'modelimportance' in R: |
| install.packages('modelimportance', repos = c('https://mkim425.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mkim425/modelimportance/issues
Pkgdown/docs site:https://mkim425.github.io
Datasets:
- forecast_data_example - Example forecast outputs for modelimportance article vignette
- forecast_data_ma_h1 - Forecast outputs for Massachusetts
- forecast_data_raw - Raw forecast outputs for get-started vignette
- target_data_example - Example target data for modelimportance article vignette
- target_data_ma - Target data for Massachusetts used in vignette runtime data
- target_data_raw - Raw target data for get-started vignette
Last updated from:fc72a2004c. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 259 | ||
| source / vignettes | OK | 253 | ||
| linux-release-x86_64 | OK | 195 | ||
| macos-release-arm64 | OK | 202 | ||
| macos-oldrel-arm64 | OK | 287 | ||
| windows-devel | OK | 162 | ||
| windows-release | OK | 163 | ||
| windows-oldrel | OK | 221 | ||
| wasm-release | OK | 138 |
Exports:model_importance
Dependencies:askpassbackportscachemcheckmateclicodetoolscpp11curldata.tabledigestdistfromqdplyrevaluatefarverfastmapfsfurrrfuturegenericsggplot2gitcredsglobalsgluegtablehighrhttr2hubEnsembleshubEvalshubUtilsiniisobandjsonliteknitrlabelinglifecyclelistenvmagrittrMASSmatrixStatsmemoiseopensslparallellypillarpkgconfigpurrrR6RColorBrewerRcppRcppArmadillorlangS7scalesscoringRulesscoringutilsstringistringrsystibbletidyrtidyselectutf8vctrsviridisLitewithrxfunyamlzeallot
modelimportance: Evaluating model importance within a multi-model ensemble in R
Last update: 2026-06-04
Started: 2026-02-10
Simple working examples
Setup | Example data | Evaluation using LOMO algorithm | Evaluation using LASOMO algorithm | References
Last update: 2026-05-29
Started: 2026-02-10
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Aggregate model importance scores across tasks to compute overall importance for each model | aggregate.model_imp_tbl |
| Example forecast outputs for modelimportance article vignette | forecast_data_example |
| Forecast outputs for Massachusetts, horizon 1, used in vignette runtime data | forecast_data_ma_h1 |
| Raw forecast outputs for get-started vignette | forecast_data_raw |
| Quantifies the contribution of ensemble component models to ensemble prediction accuracy for each prediction task. | model_importance |
| Print method for model importance score table | print.model_imp_tbl |
| Print method for summary of model importance score table | print.summary.model_imp_tbl |
| Summary method for model importance score table | summary.model_imp_tbl |
| Example target data for modelimportance article vignette | target_data_example |
| Target data for Massachusetts used in vignette runtime data | target_data_ma |
| Raw target data for get-started vignette | target_data_raw |
