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June, 1986 A Bayes Procedure for the Identification of Univariate Time Series Models
D. S. Poskitt
Ann. Statist. 14(2): 502-516 (June, 1986). DOI: 10.1214/aos/1176349935

Abstract

This paper is concerned with model selection in time series analysis. An identification criterion is presented that is asymptotically equivalent to a Bayes decision rule. The discussion is conducted in the context of a general class of parametric time series models and consideration is given to the special case of order determination in autoregressive moving-average representations. Consistency of the criterion is proved.

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D. S. Poskitt. "A Bayes Procedure for the Identification of Univariate Time Series Models." Ann. Statist. 14 (2) 502 - 516, June, 1986. https://doi.org/10.1214/aos/1176349935

Information

Published: June, 1986
First available in Project Euclid: 12 April 2007

zbMATH: 0603.62093
MathSciNet: MR840511
Digital Object Identifier: 10.1214/aos/1176349935

Subjects:
Primary: 62M10
Secondary: 62C10

Rights: Copyright © 1986 Institute of Mathematical Statistics

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Vol.14 • No. 2 • June, 1986
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