Installation
About
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.
gitlab.com/dashaub/forecastHybrid | |
github.com/ellisp/forecastHybrid | |
Bug report | File report |
Key Metrics
Downloads
Yesterday | 272 0% |
Last 7 days | 1.713 +24% |
Last 30 days | 5.987 -45% |
Last 90 days | 22.879 +37% |
Last 365 days | 78.094 -48% |