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:Dr. Ranjit Kumar Paul [aut], Dr. Md Yeasin [aut, cre]

WeightedEnsemble_0.1.0.tar.gz
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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)

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1 exports 0.71 score 1 dependencies 2 dependents 399 downloads

Last updated 1 years agofrom:5131e798b7. Checks:OK: 7. Indexed: yes.

Exports:WeightedEnsemble

Dependencies:metaheuristicOpt