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

Keywords

AUTOCORRELATION FUNCTIONAUTOREGRESSIVE MOVING AVERAGE PROCESSCRAMÉR-WOLD FACTORIZATIONSEASONAL TIME SERIES

Information

Type
Research Papers
Information
Journal of Applied Probability , Volume 14 , Issue 4 , December 1977 , pp. 785 - 794
Copyright
Copyright © Applied Probability Trust 1977 

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References

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