gen.garma.wge: Function to generate a GARMA realization

In tswge: Time Series for Data Science

Function to generate a GARMA realization

Description

This function calls gen.geg.wge and arima.sim

Usage

gen.garma.wge(n,u,lambda,phi = 0,theta=0,trun=300000,burn_in=600,vara=1,plot=TRUE,sn=0)

Arguments

n	the realization length to be generated
u	Parameter u in the GARMA model given in (11.16) of Woodward, Gray, and Elliott text
lambda	Parameter lambda in the GARMA model given in (11.16) of Woodward, Gray, and Elliott text
phi	vector of AR parameters of ARMA part of GARMA model
theta	vector of MA parameters of ARMA part of GARMA model using signs as given ijn the Woodward, Grayu, and Elliott text
trun	the truncation point of the infinite GLP form
burn_in	is the burning-in period for the simulation
vara	White noise variance, default=1
plot	Logical: TRUE=plot, FALSE=no plot
sn	determines the seed used in the simulation. sn=0 produces new/random realization each time. sn=positive integer produces same realization each time

Value

This function generates and (optionally plots) an GARMA realization

Author(s)

Wayne Woodward

References

"Applied Time Series Analysis with R, 2nd edition" by Woodward, Gray, and Elliott

Examples

gen.garma.wge(n=100, u=.8,lambda=.4,phi=.9)

tswge documentation built on Feb. 16, 2023, 6:51 p.m.