Forecast Combinations in R using the ForecastComb Package

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.

Christoph E. Weiss , Eran Raviv , Gernot Roetzer

Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at

CRAN packages used

BMA, opera, forecastHybrid, ForecastCombinations, GeomComb, quadprog, mtsdi, forecTheta

CRAN Task Views implied by cited packages

TimeSeries, Bayesian, Econometrics, OfficialStatistics, Optimization, SocialSciences, Survival


Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".


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

  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 = {},
  doi = {10.32614/RJ-2018-052},
  volume = {10},
  issue = {2},
  issn = {2073-4859},
  pages = {262-281}