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Methods for Determining the Order of an Autoregressive-Moving Average Process: A Survey

Jan G. de Gooijer, Bovas Abraham, Ann Gould and Lecily Robinson
International Statistical Review / Revue Internationale de Statistique
Vol. 53, No. 3 (Dec., 1985), pp. 301-329
DOI: 10.2307/1402894
Stable URL: http://www.jstor.org/stable/1402894
Page Count: 29
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Methods for Determining the Order of an Autoregressive-Moving Average Process: A Survey
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Abstract

Determining the order of an autoregressive-moving average process is an important and difficult part of time series analysis. Often time series analysts follow the Box-Jenkins approach to time series modelling. This approach relies somewhat on the subjective judgement of the analyst. Many other less heuristic methods have been proposed and used in the literature. In this survey the most important of these order determination methods are reviewed and their theoretical and practical relevance are discussed. /// Le problème du choix de l'ordre d'un modèle ARMA a été étudié depuis longtemps. Souvent la construction de ce modèle est basée sur les fonctions empiriques d'autocorrélation et d'autocorrélation partielle de Box et Jenkins. Plusieurs autres procédures sont disponsibles. Dans cet article nous passons en revue les plus importantes de ces procédures et nous examinons leurs propriétés statistiques.

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