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(), thetaf(), nnetar(), stlm(), tbats(), and snaive() can be combined with equal weights, weights based on in-sample errors (introduced by Bates & Granger (1969) <doi:10.1057/jors.1969.103>), or cross-validated weights. Cross validation for time series data with user-supplied models and forecasting functions is also supported to evaluate model accuracy.
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Description file content
- Package
- forecastHybrid
- Title
- Convenient Functions for Ensemble Time Series Forecasts
- Version
- 4.2.17
- Date
- 2019-02-11
- Description
- 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)
- Depends
- R (>= 3.1.1), forecast (>= 8.1), thief
- Imports
- doParallel (>= 1.0.10), foreach (>= 1.4.3), ggplot2 (>= 2.2.0), purrr (>= 0.2.5), zoo (>= 1.7)
- Suggests
- GMDH, knitr, rmarkdown, roxygen2, testthat
- VignetteBuilder
- knitr
- License
- GPL-3
- URL
- BugReports
- https://github.com/ellisp/forecastHybrid/issues
- LazyData
- true
- RoxygenNote
- 6.1.1
- ByteCompile
- true
- NeedsCompilation
- no
- Encoding
- UTF-8
- Packaged
- 2019-02-11 14:51:01 UTC; dashaub
- Author
- David Shaub [aut, cre], Peter Ellis [aut]
- Maintainer
- David Shaub
- Repository
- CRAN
- Date/Publication
- 2019-02-12 00:15:52 UTC
install.packages('forecastHybrid')
4.2.17
9 months ago
https://gitlab.com/dashaub/forecastHybrid
David Shaub
GPL-3
Depends on
R (>= 3.1.1), forecast (>= 8.1), thief
Imports
doParallel (>= 1.0.10), foreach (>= 1.4.3), ggplot2 (>= 2.2.0), purrr (>= 0.2.5), zoo (>= 1.7)