This paper introduces the R package ForecastComb. The aim is to provide researchers and practitioners with a comprehensive implementation of the most common ways in which forecasts can be combined. The package in its current version covers 15 popular estimation methods for creating a combined forecasts – including simple methods, regression-based methods, and eigenvector-based methods. It also includes useful tools to deal with common challenges of forecast combination (e.g., missing values in component forecasts, or multicollinearity), and to rationalize and visualize the combination results.
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2018-052.zip
BMA, opera, forecastHybrid, ForecastCombinations, GeomComb, quadprog, mtsdi, forecTheta
TimeSeries, Bayesian, Econometrics, OfficialStatistics, Optimization, SocialSciences, Survival
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For attribution, please cite this work as
Weiss, et al., "The R Journal: Forecast Combinations in R using the ForecastComb Package", The R Journal, 2018
BibTeX citation
@article{RJ-2018-052,
author = {Weiss, Christoph E. and Raviv, Eran and Roetzer, Gernot},
title = {The R Journal: Forecast Combinations in R using the ForecastComb Package},
journal = {The R Journal},
year = {2018},
note = {https://doi.org/10.32614/RJ-2018-052},
doi = {10.32614/RJ-2018-052},
volume = {10},
issue = {2},
issn = {2073-4859},
pages = {262-281}
}