VarianceRacfARz: Covariance Matrix Residual Autocorrelations for ARz
Description
The ARz subset model is defined by taking a subset of the
partial autocorrelations (zeta parameters) in the AR(p) model.
With this function one can obtain the
standard deviations of the residual autocorrelations which can
be used for diagnostic checking with RacfPlot.
Usage
VarianceRacfARz(zeta, lags, MaxLag, n)
Arguments
zeta
zeta parameters (partial autocorrelations)
lags
lags in model
MaxLag
covariance matrix for residual autocorrelations at
lags 1,...,m, where m=MaxLag is computes
n
length of time series
Value
The m-by-m covariance matrix of residual autocorrelations at lags
1,...,m, where m = MaxLag.
Details
The covariance matrix of the residual autocorrelations in the
subset ARz case is derived in McLeod and Zhang (2006, eqn. 16)
References
McLeod, A.I. and Zhang, Y. (2006).
Partial autocorrelation parameterization for subset autoregression.
Journal of Time Series Analysis, 27, 599-612.
#the standard deviations of the first 5 residual autocorrelations#to a subset AR(1,2,6) model fitted to Series A isv<-VarianceRacfARp(c(0.36,0.23,0.23),c(1,2,6), 5, 197)
sqrt(diag(v))