A Bayesian Analysis of Spectral ARMA Model. (5th July 2012)

• Record Type: Journal Article
• Authors: Bezerra, Manoel I. Silvestre; Moala, Fernando Antonio; Iano, Yuzo
• Other Names: Wong Kwok W. Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2012(2012)
• Publication Date: 2012-07-05
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2012/565894
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Bezerra et al. (2008) proposed a new method, based on Yule-Walker equations, to estimate the ARMA spectral model. In this paper, a Bayesian approach is developed for this model by using the noninformative prior proposed by Jeffreys (1967). The Bayesian computations, simulation via Markov Monte Carlo (MCMC) is carried out and characteristics of marginal posterior distributions such as Bayes estimator and confidence interval for the parameters of the ARMA model are derived. Both methods are also compared with the traditional least squares and maximum likelihood approaches and a numerical illustration with two examples of the ARMA model is presented to evaluate the performance of the procedures.