Predictive Density Order Selection of Periodic AR Models

Abstract

This article considers the order selection problem of periodic autoregressive models. Our main goal is the adaptation of the Bayesian Predictive Density Criterion (PDC), established by Djuric' and Kay (1992) for selecting the order of a stationary autoreg-ressive model, to deal with the order identification problem of a periodic autoregressive model. The performance of the established criterion, (P-PDC), is compared, via simulation studies, to the performances of some well-known existing criteria.

Keywords:

• Bayesian approach
• Non informative prior densities
• Periodic autoregressive model
• Predictive density criterion

Mathematics Subject Classification:

• 62

Acknowledgments

The authors would like to express their most sincere thanks and grateful acknowledgment to Professor N. Balakrishnan, Editor-in-Chief of Communications in Statistics—Simulation and Computation and to the anonymous referee for their fruitful suggestions and constructive remarks. Also, the first author presents his thanks to the colleague F. Hamdi for his help in the programming task.