Convenient Functions for Ensemble Time Series Forecasts
Description
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) ),
or cross-validated weights. Cross validation for time series data with user-supplied models
and forecasting functions is also supported to evaluate model accuracy.