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.
Total
13,880
Last month
850
Last week
169
Average per day
28
Daily downloads
Total downloads
Description file content
- Package
- forecastHybrid
- Title
- Convenient Functions for Ensemble Time Series Forecasts
- Version
- 1.0.8
- Date
- 2017-07-10
- Description
- 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.
- Depends
- R (>= 3.1.1), doParallel (>= 1.0.10), forecast (>= 8.1), foreach (>= 1.4.3), ggplot2 (>= 2.2.0)
- Imports
- reshape2 (>= 1.4.2), zoo (>= 1.7)
- Suggests
- knitr, rmarkdown, testthat
- VignetteBuilder
- knitr
- License
- GPL-3
- URL
- BugReports
- https://github.com/ellisp/forecastHybrid/issues
- LazyData
- true
- RoxygenNote
- 6.0.1
- ByteCompile
- true
- NeedsCompilation
- no
- Packaged
- 2017-07-10 16:41:35 UTC; david
- Author
- David Shaub [aut, cre], Peter Ellis [aut]
- Maintainer
- David Shaub
- Repository
- CRAN
- Date/Publication
- 2017-07-12 10:22:22 UTC
install.packages('forecastHybrid')
1.0.8
a month ago
https://github.com/ellisp/forecastHybrid
David Shaub
GPL-3
Depends on
R (>= 3.1.1), doParallel (>= 1.0.10), forecast (>= 8.1), foreach (>= 1.4.3), ggplot2 (>= 2.2.0)
Imports
reshape2 (>= 1.4.2), zoo (>= 1.7)