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Unique decomposition of low-order time series

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  • Eugene Seneta
  • Simon Ku

Abstract

We give necessary and sufficient conditions on the parameters of processes ARMA(1, 1) and ARMA(2, 1) for representation of each as unique sums of independent simpler ARMA processes, including deduction from the sum process of the innovation variances of these summands. This work on inversion is motivated by examples in the article of Granger and Morris (1976) and by our earlier article (Ku and Seneta, 1998), to which the present article is a self-contained sequel. The theory is illustrated by the analysis of tree ring data.

Suggested Citation

  • Eugene Seneta & Simon Ku, 2016. "Unique decomposition of low-order time series," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(11), pages 3357-3366, June.
  • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:11:p:3357-3366
    DOI: 10.1080/03610926.2014.904349
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