EBMAforecast: Estimate Ensemble Bayesian Model Averaging Forecasts using Gibbs Sampling or EM-Algorithms

Create forecasts from multiple predictions using ensemble Bayesian model averaging (EBMA). EBMA models can be estimated using an expectation maximization (EM) algorithm or as fully Bayesian models via Gibbs sampling. The methods in this package are Montgomery, Hollenbach, and Ward (2015) <doi:10.1016/j.ijforecast.2014.08.001> and Montgomery, Hollenbach, and Ward (2012) <doi:10.1093/pan/mps002>.

Version: 1.0.33
Imports: Rcpp (≥ 1.0.2), plyr, graphics, separationplot, Hmisc, abind, gtools, methods, glue
LinkingTo: Rcpp
Published: 2026-05-04
DOI: 10.32614/CRAN.package.EBMAforecast
Author: Florian M. Hollenbach ORCID iD [aut, cre], Jacob M. Montgomery [aut], Michael D. Ward [aut]
Maintainer: Florian M. Hollenbach <fho.egb at cbs.dk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/fhollenbach/EBMA/
NeedsCompilation: yes
CRAN checks: EBMAforecast results

Documentation:

Reference manual: EBMAforecast.html , EBMAforecast.pdf

Downloads:

Package source: EBMAforecast_1.0.33.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): EBMAforecast_1.0.33.tgz, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available
Old sources: EBMAforecast archive

Linking:

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