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Journal of Probability and Statistics
Volume 2017, Article ID 1235979, 12 pages
https://doi.org/10.1155/2017/1235979
Research Article

Bootstrap Order Determination for ARMA Models: A Comparison between Different Model Selection Criteria

University of California San Diego (UCSD), San Diego, CA, USA

Correspondence should be addressed to Livio Fenga; ude.dscu@agnefl

Received 31 July 2016; Accepted 19 March 2017; Published 16 April 2017

Academic Editor: Ramón M. Rodríguez-Dagnino

Copyright © 2017 Livio Fenga. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The present paper deals with the order selection of models of the class for autoregressive moving average. A novel method—previously designed to enhance the selection capabilities of the Akaike Information Criterion and successfully tested—is now extended to the other three popular selectors commonly used by both theoretical statisticians and practitioners. They are the final prediction error, the Bayesian information criterion, and the Hannan-Quinn information criterion which are employed in conjunction with a semiparametric bootstrap scheme of the type sieve.