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-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:

PWEV

Linking:

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