forecastHybrid: Convenient Functions for Ensemble Time Series Forecasts
Version 3.0.14

Convenient functions for ensemble forecasts in R combining approaches from the 'forecast' package. Forecasts generated from auto.arima(), ets(), thetam(), nnetar(), stlm(), and tbats() 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.

Package details

AuthorDavid Shaub [aut, cre], Peter Ellis [aut]
Date of publication2018-07-22 20:40:03 UTC
MaintainerDavid Shaub <[email protected]>
LicenseGPL-3
Version3.0.14
URL https://gitlab.com/dashaub/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 July 23, 2018, 1 a.m.