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(),
thetam(), nnetar(), stlm(), and tbats() can be combined with equal weights, weights
based on in-sample errors, or CV weights. Cross validation for time series data
and user-supplied models and forecasting functions is also supported to evaluate model accuracy.
Version: |
2.0.10 |
Depends: |
R (≥ 3.1.1), forecast (≥ 8.1) |
Imports: |
doParallel (≥ 1.0.10), foreach (≥ 1.4.3), ggplot2 (≥
2.2.0), reshape2 (≥ 1.4.2), zoo (≥ 1.7) |
Suggests: |
GMDH, knitr, rmarkdown, testthat |
Published: |
2018-01-03 |
Author: |
David Shaub [aut, cre],
Peter Ellis [aut] |
Maintainer: |
David Shaub <davidshaub at gmx.com> |
BugReports: |
https://github.com/ellisp/forecastHybrid/issues |
License: |
GPL-3 |
URL: |
https://github.com/ellisp/forecastHybrid |
NeedsCompilation: |
no |
Materials: |
NEWS |
In views: |
TimeSeries |
CRAN checks: |
forecastHybrid results |
Downloads:
Reverse dependencies:
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