View source: R/true.garma.aut.wge.R
true.garma.aut.wge | R Documentation |
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
true.garma.aut.wge(u,lambda,phi=0,theta=0,lag.max=50,vara=1,plot=TRUE)
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 |
For Gegenbauer model use phi=theta=0
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 |
Wayne Woodward
"Applied Time Series Analysis with R, second editon" by Woodward, Gray, and Elliott
y=true.garma.aut.wge(u=.8,lambda=.4,phi=.8)
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