CUED Publications database

Linear gaussian computations for near-exact Bayesian Monte Carlo inference in skewed alpha-stable time series models

Lemke, T and Godsill, SJ (2012) Linear gaussian computations for near-exact Bayesian Monte Carlo inference in skewed alpha-stable time series models. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. pp. 3737-3740. ISSN 1520-6149

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Abstract

In this paper we study parameter estimation for time series with asymmetric α-stable innovations. The proposed methods use a Poisson sum series representation (PSSR) for the asymmetric α-stable noise to express the process in a conditionally Gaussian framework. That allows us to implement Bayesian parameter estimation using Markov chain Monte Carlo (MCMC) methods. We further enhance the series representation by introducing a novel approximation of the series residual terms in which we are able to characterise the mean and variance of the approximation. Simulations illustrate the proposed framework applied to linear time series, estimating the model parameter values and model order P for an autoregressive (AR(P)) model driven by asymmetric α-stable innovations. © 2012 IEEE.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div F > Signal Processing and Communications
Depositing User: Cron Job
Date Deposited: 18 May 2016 19:06
Last Modified: 27 May 2016 00:37
DOI: 10.1109/ICASSP.2012.6288729