Package: garma
Type: Package
Title: Fitting and Forecasting Gegenbauer ARMA Time Series Models
Version: 0.9.7
Date: 2021-01-06
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, ggplot2
Imports: Rsolnp, pracma, signal, zoo, lubridate, crayon, utils, nloptr,
        BB, GA, dfoptim, pso, FKF, tswge
Suggests: longmemo, yardstick, tidyverse, testthat, knitr, rmarkdown
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-06 08:17:45 UTC; richard
Author: Richard Hunt [aut, cre]
Repository: CRAN
Date/Publication: 2021-01-07 03:10:03 UTC
