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garma  

Fitting and Forecasting Gegenbauer ARMA Time Series Models
View on CRAN: Click here


Download and install garma package within the R console
Install from CRAN:
install.packages("garma")

Install from Github:
library("remotes")
install_github("cran/garma")

Install by package version:
library("remotes")
install_version("garma", "0.9.23")



Attach the package and use:
library("garma")
Maintained by
Richard Hunt
[Scholar Profile | Author Map]
First Published: 2020-08-06
Latest Update: 2023-08-19
Description:
Methods for estimating univariate long memory-seasonal/cyclical Gegenbauer time series processes. See for example (2022) . Refer to the vignette for details of fitting these processes.
How to cite:
Richard Hunt (2020). garma: Fitting and Forecasting Gegenbauer ARMA Time Series Models. R package version 0.9.23, https://cran.r-project.org/web/packages/garma. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.9.2 (2020-08-06 10:10), 0.9.3 (2020-08-31 08:50), 0.9.6 (2020-10-29 09:10), 0.9.7 (2021-01-07 04:10), 0.9.8 (2021-07-22 09:40), 0.9.10 (2021-10-22 09:40), 0.9.11 (2022-02-15 11:00), 0.9.13 (2023-08-19 14:52), 0.9.20 (2024-08-23 07:00), 0.9.22 (2024-09-05 10:40), 0.9.23 (2024-09-13 05:40)
Other packages that cited garma R package
View garma citation profile
Other R packages that garma depends, imports, suggests or enhances
Complete documentation for garma
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