garma: Fitting and Forecasting Gegenbauer ARMA Time Series Models
Methods for estimating univariate long memory-seasonal/cyclical Gegenbauer time series processes. See for example (2022) <doi:10.1007/s00362-022-01290-3>. Refer to the vignette for details of fitting these processes.
| Version: | 0.9.24 |
| Depends: | forecast,ggplot2 |
| Imports: | Rsolnp,nloptr,pracma,signal,zoo,lubridate,rlang,crayon, utils |
| Suggests: | longmemo,yardstick,testthat (≥ 3.0.0),knitr,rmarkdown |
| Published: | 2025-03-16 |
| DOI: | 10.32614/CRAN.package.garma |
| Author: | Richard Hunt [aut, cre] |
| Maintainer: | Richard Hunt <maint at huntemail.id.au> |
| License: | GPL-3 |
| URL: | https://github.com/rlph50/garma |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| In views: | TimeSeries |
| CRAN checks: | garma results |
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