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forecastHybrid  

Convenient Functions for Ensemble Time Series Forecasts
View on CRAN: Click here


Download and install forecastHybrid package within the R console
Install from CRAN:
install.packages("forecastHybrid")

Install from Github:
library("remotes")
install_github("cran/forecastHybrid")

Install by package version:
library("remotes")
install_version("forecastHybrid", "5.0.19")



Attach the package and use:
library("forecastHybrid")
Maintained by
David Shaub
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-04-16
Latest Update: 2020-08-28
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) ), or cross-validated weights. Cross validation for time series data with user-supplied models and forecasting functions is also supported to evaluate model accuracy.
How to cite:
David Shaub (2016). forecastHybrid: Convenient Functions for Ensemble Time Series Forecasts. R package version 5.0.19, https://cran.r-project.org/web/packages/forecastHybrid
Previous versions and publish date:
0.1.5 (2016-04-16 04:35), 0.1.6 (2016-06-01 07:40), 0.1.7 (2016-06-06 08:08), 0.2.0 (2016-09-23 09:22), 0.3.0 (2016-12-19 08:34), 0.4.0 (2017-03-31 08:12), 0.4.1 (2017-06-18 19:49), 1.0.8 (2017-07-12 12:22), 1.1.9 (2017-08-23 20:50), 2.0.10 (2018-01-03 14:09), 2.1.11 (2018-03-28 00:30), 2.2.12 (2018-05-04 16:19), 3.0.14 (2018-07-22 22:40), 4.1.16 (2018-12-20 00:40), 4.2.17 (2019-02-12 01:15), 5.0.18 (2020-04-02 14:00)
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