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: | 1.1.9 |
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: | knitr, rmarkdown, testthat |
Published: | 2017-08-23 |
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 |
Reference manual: | forecastHybrid.pdf |
Vignettes: |
Using the "forecastHybrid" package |
Package source: | forecastHybrid_1.1.9.tar.gz |
Windows binaries: | r-devel: forecastHybrid_1.1.9.zip, r-release: forecastHybrid_1.1.9.zip, r-oldrel: forecastHybrid_1.1.9.zip |
OS X El Capitan binaries: | r-release: forecastHybrid_1.1.9.tgz |
OS X Mavericks binaries: | r-oldrel: forecastHybrid_1.1.9.tgz |
Old sources: | forecastHybrid archive |
Reverse imports: | mafs, sutteForecastR |
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