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forecastHybrid: Convenient Functions for Ensemble Time Series Forecasts
Convenient functions for ensemble forecasts in R combining approaches from the 'forecast' package. Forecasts generated from auto.arima(), ets(), thetaf(), nnetar(), stlm(), tbats(), and snaive() 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.
Getting started
Browse package contents
Package details |
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| Author | David Shaub [aut, cre], Peter Ellis [aut] |
| Maintainer | David Shaub <davidshaub@gmx.com> |
| License | GPL-3 |
| Version | 5.0.19 |
| URL | https://gitlab.com/dashaub/forecastHybrid https://github.com/ellisp/forecastHybrid |
| Package repository | View on CRAN |
| Installation |
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