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A poisson series approach to Bayesian Monte Carlo inference for skewed alpha-stable distributions

Lemke, T and Godsill, SJ (2014) A poisson series approach to Bayesian Monte Carlo inference for skewed alpha-stable distributions. In: UNSPECIFIED pp. 8023-8027..

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Abstract

In this paper we study parameter estimation for α-stable distribution parameters. The proposed approach uses a Poisson series representation (PSR) for skewed α-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 α-stable data, estimating the distribution parameter values. © 2014 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Subjects: UNSPECIFIED
Divisions: Div F > Signal Processing and Communications
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:16
Last Modified: 23 Nov 2017 03:33
DOI: