Markov chain Monte Carlo estimation of autoregressive models with application to metal pollutant concentration in sludge

Authors:
G. Barnett;R. Kohn;S. Sheather;J. Wong
Affiliations:
Australian Graduate School of Management University of New South Wales Kensington, NSW, Australia;Australian Graduate School of Management University of New South Wales Kensington, NSW, Australia;Australian Graduate School of Management University of New South Wales Kensington, NSW, Australia;Department of Chemistry, University of Sydney Camperdown, NSW, Australia
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
1995

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Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images

IEEE Transactions on Pattern Analysis and Machine Intelligence

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Abstract

This paper provides an introduction to and an overview of Bayesian estimation, based on Markov chain Monte Carlo techniques. Autoregressive time series models are considered in some detail. Finally, an example involving the modelling of a metal pollutant concentration in sludge is presented.