gen.glambda.wge: Function to generate a g(lambda) realization

In BivinSadler/tswge: Time Series for Data Science

Function to generate a g(lambda) realization

Description

This function generates a g(lambda) TVF realization as discussed in Chapter 13 of Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott

Usage

gen.glambda.wge(n, lambda, phi =0, offset = 20, vara = 1, plot = TRUE, sn = 0)

Arguments

n	Length of realization to be generated
lambda	The lambda involved in the g(lambda) time transformation - see Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott
phi	Vector of AR coefficients
vara	White noise variance, default=1
offset	The offset parameter in a g(lambda) process. See section 13.2 in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott
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 simply generates and (optionally plots) an ARMA realization

Author(s)

Wayne Woodward

References

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

Examples

gen.glambda.wge(n=500, lambda=0.5,phi=c(1.9,-.99), vara=1, plot=TRUE,sn=0)

BivinSadler/tswge documentation built on Sept. 15, 2023, 4:07 p.m.