Package: garma
Type: Package
Title: Fitting and Forecasting Gegenbauer ARMA Time Series Models
Version: 0.9.2
Date: 2020-07-26
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 long memory-seasonal/cyclical Gegenbauer univariate 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
Encoding: UTF-8
LazyData: true
Imports: assertthat, zoo, forecast, lubridate, FKF, signal, pracma,
        nloptr, Rsolnp, ggplot2, Rdpack (>= 0.7)
Suggests: longmemo, tidyverse, BB, GA, pso, dfoptim, testthat, knitr,
        rmarkdown
RoxygenNote: 7.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-08-02 02:21:38 UTC; richard
Author: Richard Hunt [aut, cre]
Repository: CRAN
Date/Publication: 2020-08-06 08:10:02 UTC
Built: R 4.0.2; ; 2020-08-06 12:24:09 UTC; windows
