Convenient Functions for Ensemble Time Series Forecasts R package forecastHybrid version 5.1.21 CRAN Task View: TimeSeries (https://CRAN.R-project.org/view=TimeSeries) Convenient functions for ensemble forecasts in R combining approaches from the 'forecast' package. Forecasts generated from auto.arima(), ets(), thetaf(), nnetar(), stlm(), tbats(), snaive() and arfima() can be combined with equal weights, weights based on in-sample errors (introduced by Bates & Granger (1969) <doi:10.1057/jors.1969.103>), or cross-validated weights. Cross validation for time series data with user-supplied models and forecasting functions is also supported to evaluate model accuracy. Software Depends: R (>= 4.0.4), forecast (>= 8.16), thief Imports: doParallel (>= 1.0.16), foreach (>= 1.5.1), ggplot2 (>= 3.3.6), purrr (>= 0.3.5), zoo (>= 1.8) Suggests: GMDH, knitr, rmarkdown, roxygen2, testthat David Shaub <davidshaub@alumni.harvard.edu> Comprehensive R Archive Network (CRAN) David Shaub [aut, cre], Peter Ellis [aut] GPL-3 2026-01-15 application/tgz https://CRAN.R-project.org/package=forecastHybrid doi:10.32614/CRAN.package.forecastHybrid