A Bayes Procedure for the Identification of Univariate Time Series Models
The Annals of Statistics · 1986 · Volume 14 · Issue 2
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.
Keywords
62C10, 62M10, autoregressive moving-average representation, Bayes decision rule, consistency, model selection criterion, power spectrum, time series model
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