Package: forecastHybrid
Title: Convenient Functions for Ensemble Time Series Forecasts
Version: 5.0.19
Date: 2020-08-27
Authors@R: c(
   person("David", "Shaub", email = "davidshaub@gmx.com", role = c("aut", "cre")),
   person("Peter", "Ellis", email = "peter.ellis2013nz@gmail.com", role = c("aut"))
   )
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) <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.
Depends: R (>= 3.1.1), forecast (>= 8.12), 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: https://gitlab.com/dashaub/forecastHybrid,
        https://github.com/ellisp/forecastHybrid
BugReports: https://github.com/ellisp/forecastHybrid/issues
LazyData: true
RoxygenNote: 7.1.1
ByteCompile: true
NeedsCompilation: no
Encoding: UTF-8
Packaged: 2020-08-27 17:42:55 UTC; dashaub
Author: David Shaub [aut, cre],
  Peter Ellis [aut]
Maintainer: David Shaub <davidshaub@gmx.com>
Repository: CRAN
Date/Publication: 2020-08-28 06:30:03 UTC
Built: R 4.1.3; ; 2023-04-17 19:57:14 UTC; windows
