Learn R Programming

FitAR (version 1.94)

InformationMatrixARz: Fisher Information Matrix Subset Case, ARz

Description

Computes the large-sample Fisher information matrix per observation for the AR coefficients in a subset AR when parameterized by the partial autocorrelations.

Usage

InformationMatrixARz(zeta, lags)

Arguments

zeta
vector of coefficients, ie. partial autocorrelations at lags specified in the argument lags
lags
lags in subset model, same length as zeta argument

Value

a p-by-p Toeplitz matrix, p=length(zeta)

Details

The details of the computation are given in McLeod and Zhang (2006, eqn 13). FitAR uses InformationMatrixARz to obtain estimates of the standard errors of the estimated parameters in the subset AR model when partial autocorrelation parameterization is used.

References

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

See Also

FitAR, InformationMatrixAR, InformationMatrixARp

Examples

Run this code
#Information matrix for ARz(1,4) with parameters 0.9 and 0.9.
InformationMatrixARz(c(0.9, 0.9), lags=c(1,4))

Run the code above in your browser using DataLab