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
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

Documentation:

Reference manual: WeightedEnsemble.pdf

Downloads:

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

Reverse dependencies:

Reverse imports: PWEV

Linking:

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