Efficiency of the ِApproximate Bayesian Prediction of ARMA Models: A Simulation Study | ||||
| The Egyptian Statistical Journal | ||||
| Article 1, Volume 52, Issue 2, December 2008, Page 56-75 PDF (6.06 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/esju.2008.315419 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Emad El-Din A. Soliman* | ||||
| Department of Statistics, Faculty of Economics & Political Science, Cairo University, Egypt. | ||||
| Abstract | ||||
| This paper is interested in the Efficiency of the approximate Bayesian Prediction of ARMA Models. Three different approximate one step-ahead predictive densities using three different approximate are considered. These approximations are proposed by Newbold (1973), Zellner and Reynolds (1978) and Broemeling and Shaarawy (1988). Simulation is employed to study and compare the performance of the three approximate one-ahead predictive densities using some ARMA models. Simulation results show that, there is no remarkable difference between the three approximate one-ahead predictive densities in their efficiency. Moreover, their first two moment converge to those of the exact one step-ahead predictive density. | ||||
| Keywords | ||||
| ARMA models; Newbold approximation; Zellner and Reynolds approximation; Broemeling and Shaarawy approximation | ||||
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