forecastHybrid: Convenient Functions for Ensemble Time Series Forecasts (original) (raw)
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.
| Version: | 5.1.20 |
|---|---|
| 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 |
| Published: | 2025-07-06 |
| DOI: | 10.32614/CRAN.package.forecastHybrid |
| Author: | David Shaub [aut, cre], Peter Ellis [aut] |
| Maintainer: | David Shaub |
| BugReports: | https://github.com/ellisp/forecastHybrid/issues |
| License: | GPL-3 |
| URL: | https://gitlab.com/dashaub/forecastHybrid,https://github.com/ellisp/forecastHybrid |
| NeedsCompilation: | no |
| Materials: | NEWS |
| In views: | TimeSeries |
| CRAN checks: | forecastHybrid results |
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