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On the autocorrelation structure for seasonal moving average models and its implications for the Cramér-Wold factorization

Published online by Cambridge University Press:  14 July 2016

E. J. Godolphin*
Affiliation:
Royal Holloway College, London

Abstract

An account is given of the autocorrelation theory of seasonal moving average models, using a vector representation defined by the author. It is shown that the autocorrelation structure of a seasonal moving average is reducible to that of a certain non-seasonal moving average, independently of the value of the seasonal periodicity if sufficiently large. It is pointed out that existing methods for the Cramér–Wold factorization discussed in Godolphin (1976) can easily be adapted to contend with the seasonal case.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1977 

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