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(), 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.
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9.72 score 81 stars 1 dependents 152 scripts 2.6k downloadsTcomp - Data from the 2010 Tourism Forecasting Competition
The 1311 time series from the tourism forecasting competition conducted in 2010 and described in Athanasopoulos et al. (2011) <DOI:10.1016/j.ijforecast.2010.04.009>.
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5.64 score 6 stars 1 dependents 49 scripts 272 downloads