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A comparison of some of pattern identification methods for order determination of mixed ARMA models

✍ Scribed by Wai-Sum Chan

Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
104 KB
Volume
42
Category
Article
ISSN
0167-7152

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✦ Synopsis

Model identiÿcation is a crucial step in time-series modelling. The orthodox Box-Jenkins (BJ) identiÿcation examines the patterns of the sample autocorrelation function (SACF) and the sample partial autocorrelation function (SPACF). However, for mixed ARMA processes, the SACF and SPACF often exhibit similar behaviour, which makes the identiÿcation much more di cult. Recently, identiÿcation methods using the patterns of some functions of the autocorrelations have been proposed to supplement the BJ methods. This paper studies some of these proposed procedures. Their performances for order selection of a mixed ARMA process are compared with an expert system in a simulation study. Comments on each individual identiÿcation method are also given.

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