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An algorithm for computing the asymptotic fisher information matrix for seasonal SISO models

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Author Info
André Klein
Guy Mélard
Abstract

The paper presents an algorithm for computing the asymptotic Fisher information matrix of a possibly seasonal single-input single-output (SISO) time-series model. That matrix is a block matrix whose elements are basically integrals of rational functions over the oriented unit circle. The procedure makes use of the autocovariance or the cross-covariance function of two autoregressive processes based on the same noise. The algorithm also works when the input variable is omitted, the case of a seasonal ARMA model. Copyright 2004 Blackwell Publishing Ltd.

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Article provided by Blackwell Publishing in its journal Journal of Time Series Analysis.

Volume (Year): 25 (2004)
Issue (Month): 5 (09)
Pages: 627-648
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Handle: RePEc:bla:jtsera:v:25:y:2004:i:5:p:627-648

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This page was last updated on 2009-12-19.


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