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>.

Version: 0.1.0
Imports: stats, metaheuristicOpt
Published: 2023-04-10
DOI: 10.32614/CRAN.package.WeightedEnsemble
Author: Dr. Ranjit Kumar Paul [aut], Dr. Md Yeasin [aut, cre]
Maintainer: Dr. Md Yeasin <yeasin.iasri at gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: WeightedEnsemble results


Reference manual: WeightedEnsemble.pdf


Package source: WeightedEnsemble_0.1.0.tar.gz
Windows binaries: r-devel: WeightedEnsemble_0.1.0.zip, r-release: WeightedEnsemble_0.1.0.zip, r-oldrel: WeightedEnsemble_0.1.0.zip
macOS binaries: r-release (arm64): WeightedEnsemble_0.1.0.tgz, r-oldrel (arm64): WeightedEnsemble_0.1.0.tgz, r-release (x86_64): WeightedEnsemble_0.1.0.tgz, r-oldrel (x86_64): WeightedEnsemble_0.1.0.tgz

Reverse dependencies:

Reverse imports: EEML, PWEV


Please use the canonical form https://CRAN.R-project.org/package=WeightedEnsemble to link to this page.