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Journal of the American Statistical Association Volume 90, 1995 - Issue 430
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Theory and Method

Bayesian Inference for Stable Distributions

D. J. Buckle Capital Markets Research, J. P. Morgan Investment Management Inc., Almack House, 28 King Street, London, SW1Y 6XA, UK
Pages 605-613 | Received 01 Feb 1993, Published online: 27 Feb 2012
 
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Abstract

Very little work on stable distribution parameter estimation and inference appears in the literature due to the nonexistence of the probability density function. This has led in particular to a dearth of Bayesian work in this area. But Bayesian computation via Markov chain Monte Carlo allows us to sample from the distribution of the parameters of the stable distributions, by exploiting a particular mathematical representation involving the stable density.

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