The R Journal: accepted article

This article will be copy edited and may be changed before publication.

Forecast Combinations in R using the ForecastComb Package PDF download
Christoph E. Weiss, Eran Raviv and Gernot Roetzer

Abstract 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.

Received: 2017-12-20; online 2018-12-07, supplementary material, (1.2 Kb)
CRAN packages: BMA, opera, forecastHybrid, ForecastCombinations, GeomComb, quadprog, mtsdi, forecTheta
CRAN Task Views implied by cited CRAN packages: TimeSeries, Bayesian, Econometrics, OfficialStatistics, Optimization, SocialSciences, Survival


CC BY 4.0
This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2018-052,
  author = {Christoph E. Weiss and Eran Raviv and Gernot Roetzer},
  title = {{Forecast Combinations in R using the ForecastComb Package}},
  year = {2018},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2018-052},
  url = {https://journal.r-project.org/archive/2018/RJ-2018-052/index.html}
}