Fitting and Forecasting Gegenbauer ARMA Time Series Models

Methods for estimating univariate long memory-seasonal/cyclical Gegenbauer time series processes. See for example (2018) . Refer to the vignette for details of fitting these processes.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("garma")

0.9.8 by Richard Hunt, 14 days ago


https://github.com/rlph50/garma


Browse source code at https://github.com/cran/garma


Authors: Richard Hunt [aut, cre]


Documentation:   PDF Manual  


Task views: Time Series Analysis


GPL-3 license


Imports Rsolnp, pracma, signal, zoo, lubridate, crayon, utils, nloptr, BB, GA, dfoptim, pso, FKF, tswge

Depends on forecast, ggplot2

Suggests longmemo, yardstick, tidyverse, testthat, knitr, rmarkdown


See at CRAN