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An algorithm for computing the asymptotic fisher information matrix for seasonal SISO models
Author(s) -
Klein André,
Mélard Guy
Publication year - 2004
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2004.01863.x
Subject(s) - autocovariance , mathematics , fisher information , autoregressive model , autoregressive–moving average model , covariance matrix , matrix (chemical analysis) , series (stratigraphy) , algorithm , statistics , mathematical analysis , paleontology , materials science , fourier transform , biology , composite material
. 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.