true.garma.aut.wge: True GARMA autocorrelations

In tswge: Time Series for Data Science

True GARMA autocorrelations

Description

Calculate the autocovariances and autocorrelations and optionally plot the true autocorrelations of a 1-factor based on formula(11.25) of "Applied Time Series Analysis with R, second editon" Woodward, Gray, and Elliott

Usage

true.garma.aut.wge(u,lambda,phi=0,theta=0,lag.max=50,vara=1,plot=TRUE)

Arguments

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 in the Woodward, Gray, and Elliott text
lag.max	Maximum lag at which the autocorrelations and autocovariances will be calculated
vara	White noise variance
plot	Logical: TRUE=plot, FALSE=no plot

Details

For Gegenbauer model use phi=theta=0

Value

acf	Vector of length max.lag+1 containing true autocorrelations at lags 0, 1, ..., lag.max
acv	Vector of length max.lag+1 containing true autocovariances at lags 0, 1, ..., lag.max

Author(s)

Wayne Woodward

References

"Applied Time Series Analysis with R, second editon" by Woodward, Gray, and Elliott

Examples

y=true.garma.aut.wge(u=.8,lambda=.4,phi=.8)

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