Identification of Refined ARMA Echelon Form Models for Multivariate Time Series
AbstractIn the present article, we are interested in the identification of canonical ARMA echelon form models represented in a "refined" form. An identification procedure for such models is given by Tsay (J. Time Ser. Anal.10(1989), 357-372). This procedure is based on the theory of canonical analysis. We propose an alternative procedure which does not rely on this theory. We show initially that an examination of the linear dependency structure of the rows of the Hankel matrix of correlations, with originkin (i.e., with correlation at lagkin position (1,Â 1)), allows us not only to identify the Kronecker indicesn1,Â ...,Â nd, whenk=1, but also to determine the autoregressive ordersp1,Â ...,Â pd, as well as the moving average ordersq1,Â ...,Â qdof the ARMA echelon form model by settingk>1 andk
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Multivariate Analysis.
Volume (Year): 56 (1996)
Issue (Month): 2 (February)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Melard, Guy & Roy, Roch & Saidi, Abdessamad, 2006. "Exact maximum likelihood estimation of structured or unit root multivariate time series models," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 2958-2986, July.
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