Convenient functions for ensemble forecasts in R combining approaches from the 'forecast' package. Forecasts generated from auto.arima(), ets(), nnetar(), stlm(), and tbats() can be combined with equal weights or weights based on in-sample errors. Future methods such as cross validation are planned.
| Version: | 0.3.0 |
| Depends: | R (≥ 3.1.1), ggplot2 (≥ 2.2.0), forecast (≥ 7.3) |
| Imports: | reshape2 (≥ 1.4.2) |
| Suggests: | knitr, rmarkdown, testthat |
| Published: | 2016-12-19 |
| 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_0.3.0.tar.gz |
| Windows binaries: | r-devel: forecastHybrid_0.3.0.zip, r-release: forecastHybrid_0.3.0.zip, r-oldrel: forecastHybrid_0.3.0.zip |
| OS X Mavericks binaries: | r-release: forecastHybrid_0.3.0.tgz, r-oldrel: forecastHybrid_0.3.0.tgz |
| Old sources: | forecastHybrid archive |
| Reverse imports: | mafs |
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