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

.  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 procedur...

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Bibliographic Details
Published in:Journal of time series analysis 2004-09, Vol.25 (5), p.627-648
Main Authors: Klein, André, Mélard, Guy
Format: Article
Language:English
Subjects:
Algorithms
Asymptotic methods
Econometrics
Fisher information matrix
Information
Mathematical analysis
Primary 62M10
Seasons
secondary 62F15
SISO model
Statistical methods
Time series
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Summary:.  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.
ISSN:0143-9782
1467-9892
DOI:10.1111/j.1467-9892.2004.01863.x