VarianceRacfARz(FitAR)R Documentation

Covariance matrix residual autocorrelations subset AR-zeta

Description

The AR-zeta 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

Details

The covariance matrix of the residual autocorrelations in the subset AR-zeta case is derived in McLeod and Zhang (2006, eqn. 16)

Value

the m-by-m covariance matrix of residual autocorrelations at lags 1,...,m, where m=MaxLag.

Author(s)

A.I. McLeod

References

McLeod, A.I. and Zhang, Y. (2006). Partial autocorrelation parameterization for subset autoregression. Journal of Time Series Analysis, 27, 599-612.

See Also

VarianceRacfAR, VarianceRacfARz, RacfPlot

Examples

#the standard deviations of the first 5 residual autocorrelations
#to a subset AR(1,2,6) model fitted to Series A is
v<-VarianceRacfARp(c(0.36,0.23,0.23),c(1,2,6), 5, 197)
sqrt(diag(v))

[Package FitAR version 1.0 Index]