Package: forecastHybrid
Title: Convenient Functions for Ensemble Time Series Forecasts
Version: 4.1.16
Date: 2018-12-19
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(),
    thetam(), nnetar(), stlm(), and tbats() 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 (>= 8.1),
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
BugReports: https://github.com/ellisp/forecastHybrid/issues
LazyData: true
RoxygenNote: 6.1.1
ByteCompile: true
NeedsCompilation: no
Packaged: 2018-12-19 05:58:44 UTC; dashaub
Author: David Shaub [aut, cre],
  Peter Ellis [aut]
Maintainer: David Shaub <davidshaub@gmx.com>
Repository: CRAN
Date/Publication: 2018-12-19 23:40:08 UTC
