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Activity Number: 535
Type: Contributed
Date/Time: Thursday, August 10, 2006 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #306246
Title: Bayesian Parameter Estimation of Stable Distributions
Author(s): Ece Oral*+ and Cenap Erdemir
Companies: Hacettepe University and Hacettepe University
Address: Institute for Graduate Studies in Science and Engineering, 06532, Ankara, , Turkey
Keywords: stable distribution ; characteristic exponent ; distribution functions ; parameter estimation ; Metropolis-Hastings algorithm ; posterior distribution
Abstract:

Stable distributions are widely used in modeling heavy tailed data. There are many estimation methods for the parameters of stable distributions. In this study, the Bayesian approaches using Metropolis random walk chain (Tsionas, 2000) are employed and the posterior distributions of the parameters are produced. The likelihood function required for Bayesian estimation is computed by the program described by Nolan (1997). The performance of the method is investigated by simulation and a numerical example illustrated on real life data.

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