gen.aruma.wge: Function to generate an ARUMA (or ARMA or ARIMA) realization

In tswge: Time Series for Data Science

Function to generate an ARUMA (or ARMA or ARIMA) realization

Description

This function calls arima.sim but an a similar manner to gen.ns.arma.wge and gen.ns.arima.wge but allows for generation of realizations from ARUMA models (see Chapter 5 of "Applied Time Series Analysis with R, 2nd edition" by Woodward, Gray, and Elliott

Usage

gen.aruma.wge(n,phi=0,theta=0,d=0,s=0,lambda=0,vara=1,plot=TRUE,sn=0)

Arguments

n	Length of realization to be generated
phi	Vector of AR coefficients
theta	Vector of MA coefficients
d	Order of the difference
s	Order of seasonal operator
lambda	Vector of nonstaionary coefficients not associated with d or s (see Def. 5.1(b) in Woodward, Gray, and Elliott text)
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 ARMA or ARIMA or ARUMA realization

Author(s)

Wayne Woodward

References

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

Examples

gen.aruma.wge(n=100,phi=.7,theta=0, d=1, s=4,lambda=c(1.8,-1),vara=1, plot=TRUE)

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