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ts.extend  

Stationary Gaussian ARMA Processes and Other Time-Series Utilities
View on CRAN: Click here


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

Install from Github:
library("remotes")
install_github("cran/ts.extend")

Install by package version:
library("remotes")
install_version("ts.extend", "0.1.1")



Attach the package and use:
library("ts.extend")
Maintained by
Ben ONeill
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-10-28
Latest Update: 2023-02-27
Description:
Stationary Gaussian ARMA processes and the stationary GARMA distribution are fundamental in time series analysis. Here we give utilities to computethe auto-covarianceauto-correlation for a stationary Gaussian ARMA process as well as the probability functions density cumulative distribution randomgeneration for random vectors from this distribution. We also give functions for the spectral intensity and the permutation-spectrum test for testinga time-series vector for the presence of a signal.
How to cite:
Ben ONeill (2020). ts.extend: Stationary Gaussian ARMA Processes and Other Time-Series Utilities. R package version 0.1.1, https://cran.r-project.org/web/packages/ts.extend
Previous versions and publish date:
0.1.0 (2020-10-28 09:30), 0.1.1 (2020-11-14 22:50)
Other packages that cited ts.extend R package
View ts.extend citation profile
Other R packages that ts.extend depends, imports, suggests or enhances
Functions, R codes and Examples using the ts.extend R package
Some associated functions: ARMA.autocov . ARMA.var . dGARMA . garma . intensity . pGARMA . plot.intensity . plot.spectrum.test . plot.time.series . rGARMA . spectrum.test . 
Some associated R codes: ARMA.autocov.R . ARMA.var.R . dGARMA.R . data.R . intensity.R . pGARMA.R . plot.intensity.R . plot.spectrum.test.R . plot.time.series.R . rGARMA.R . spectrum.test.R .  Full ts.extend package functions and examples
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