InformationMatrixARz: Fisher Information Matrix Subset Case, ARz

In FitAR: Subset AR Model Fitting

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

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.

Value

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

Author(s)

A.I. McLeod and Y. Zhang

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

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

FitAR documentation built on May 2, 2019, 3:22 a.m.