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]>
LicenseGPL-3
Version4.2.17
URL https://gitlab.com/dashaub/forecastHybrid https://github.com/ellisp/forecastHybrid
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("forecastHybrid")

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forecastHybrid documentation built on May 2, 2019, 4:02 a.m.