Package: garma
Type: Package
Title: Fitting and Forecasting Gegenbauer ARMA Time Series Models
Version: 0.9.6
Date: 2020-10-09
Authors@R: person("Richard", "Hunt", email = "maint@huntemail.id.au",
  role = c("aut", "cre"))
Maintainer: Richard Hunt <maint@huntemail.id.au>
Description: Methods for estimating univariate long memory-seasonal/cyclical
             Gegenbauer time series processes. See for example (2018) <doi:10.1214/18-STS649>.
             Refer to the vignette for details of fitting these processes.
License: GPL-3
URL: https://github.com/rlph50/garma
Encoding: UTF-8
LazyData: true
Depends: forecast
Imports: Rsolnp, ggplot2, pracma, signal, zoo, lubridate, FKF, nloptr,
        crayon, utils
Suggests: longmemo, yardstick, tidyverse, BB, GA, pso, dfoptim,
        testthat, knitr, rmarkdown
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-10-29 07:47:58 UTC; richard
Author: Richard Hunt [aut, cre]
Repository: CRAN
Date/Publication: 2020-10-29 08:10:02 UTC
