forecastHybrid (4.2.17)

Convenient Functions for Ensemble Time Series Forecasts.

https://gitlab.com/dashaub/forecastHybrid
https://github.com/ellisp/forecastHybrid
http://cran.r-project.org/web/packages/forecastHybrid

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.

Maintainer: David Shaub
Author(s): David Shaub [aut, cre], Peter Ellis [aut]

License: GPL-3

Uses: doParallel, foreach, forecast, ggplot2, purrr, thief, zoo, testthat, roxygen2, knitr, rmarkdown, GMDH

Released 10 months ago.