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.

Package details

AuthorDavid Shaub [aut, cre], Peter Ellis [aut]
MaintainerDavid Shaub <[email protected]>
Package repositoryView on CRAN
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forecastHybrid documentation built on May 2, 2019, 4:02 a.m.