Package: WeightedEnsemble 0.1.0
WeightedEnsemble: Weighted Ensemble for Hybrid Model
The weighted ensemble method is a valuable approach for combining forecasts. This algorithm employs several optimization techniques to generate optimized weights. This package has been developed using algorithm of Armstrong (1989) <doi:10.1016/0024-6301(90)90317-W>.
Authors:
WeightedEnsemble_0.1.0.tar.gz
WeightedEnsemble_0.1.0.zip(r-4.5)WeightedEnsemble_0.1.0.zip(r-4.4)WeightedEnsemble_0.1.0.zip(r-4.3)
WeightedEnsemble_0.1.0.tgz(r-4.4-any)WeightedEnsemble_0.1.0.tgz(r-4.3-any)
WeightedEnsemble_0.1.0.tar.gz(r-4.5-noble)WeightedEnsemble_0.1.0.tar.gz(r-4.4-noble)
WeightedEnsemble_0.1.0.tgz(r-4.4-emscripten)WeightedEnsemble_0.1.0.tgz(r-4.3-emscripten)
WeightedEnsemble.pdf |WeightedEnsemble.html✨
WeightedEnsemble/json (API)
# Install 'WeightedEnsemble' in R: |
install.packages('WeightedEnsemble', repos = c('https://yeasinstat.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:5131e798b7. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 20 2024 |
R-4.5-win | OK | Nov 20 2024 |
R-4.5-linux | OK | Nov 20 2024 |
R-4.4-win | OK | Nov 20 2024 |
R-4.4-mac | OK | Nov 20 2024 |
R-4.3-win | OK | Nov 20 2024 |
R-4.3-mac | OK | Nov 20 2024 |
Exports:WeightedEnsemble
Dependencies:metaheuristicOpt
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Weighted Ensemble for Hybrid Model | WeightedEnsemble |