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2014
Conference Paper
Titel
A poisson series approach to Bayesian Monte Carlo inference for skewed alpha-stable distributions
Abstract
In this paper we study parameter estimation for a-stable distribution parameters. The proposed approach uses a Poisson series representation (PSR) for skewed a-stable random variables, which provides a conditionally Gaussian framework. Therefore, a straightforward implementation of Bayesian parameter estimation using Markov chain Monte Carlo (MCMC) methods is feasible. To extend the series representation to practical application, we provide a novel approximation of the series residual terms, which exactly characterises the mean and variance of the approximation and maintains its structure. Simulations illustrate the proposed framework applied to skewed a-stable data, estimating the distribution parameter values.