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- W4245430995 abstract "Analysis of time-series models has, in the past, concentrated mainly on second-order properties, i.e. the covariance structure. Recent interest in non-Gaussian and non-linear processes has necessitated exploration of more general properties, even for standard models. We demonstrate that the powerful Markov property which greatly simplifies the distributional structure of finite autoregressions has an analogue in the (non-Markovian) finite moving-average processes. In fact, all the joint distributions of samples of a q th-order moving average may be constructed from only the ( q + 1)th-order distribution. The usefulness of this result is illustrated by references to three areas of application: time-reversibility; asymptotic behaviour; and sums and associated point and count processes. Generalizations of the result are also considered." @default.
- W4245430995 created "2022-05-12" @default.
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- W4245430995 date "1988-06-01" @default.
- W4245430995 modified "2023-09-25" @default.
- W4245430995 title "The distributional structure of finite moving-average processes" @default.
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- W4245430995 doi "https://doi.org/10.1017/s002190020004095x" @default.
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