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FitAR (version 1.94)

VarianceRacfAR: Covariance Matrix Residual Autocorrelations for AR

Description

Computes the variance-covariance matrix for the residual autocorrelations in an AR(p).

Usage

VarianceRacfAR(phi, MaxLag, n)

Arguments

phi
vector of AR coefficients
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 for the residual autocorrelations is derived in McLeod (1978, eqn. 15) for the general ARMA case. With this function one can obtain the standard deviations of the residual autocorrelations which can be used for diagnostic checking with RacfPlot.

References

McLeod, A.I. (1978), On the distribution and applications of residual autocorrelations in Box-Jenkins modelling, Journal of the Royal Statistical Society B, 40, 296--302

See Also

VarianceRacfARp, VarianceRacfARz, RacfPlot

Examples

Run this code
VarianceRacfAR(0.5,5,100)

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