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Dynamic lattice-Markov spatio-temporal models for environmental data

Lookup NU author(s): Linda Garside, Professor Darren Wilkinson

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Abstract

This paper is concerned with the modelling of the latent structure of a Bayesian spatio-temporal model with a view to improving parameter inference, smoothing and prediction. The equilibrium distribution of a time stationary system will be examined, paying particular attention to edge-effects and the effect of grid-coarsening. In order to develop an effective MCMC algorithm, the latent process is integrated out of the model. These techniques will be illustrated using North Atlantic ocean temperature data.


Publication metadata

Author(s): Garside LM, Wilkinson DJ

Editor(s): Bernardo, J.M., Bayarri, M.J., Berger, J.O., Dawid, A.P., Heckerman, D., Smith, A.F.M.

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Bayesian Statistics: 7th Valencia International Meeting on Bayesian Statistics

Year of Conference: 2003

Pages: 535-542

Publisher: Oxford University Press

Library holdings: Search Newcastle University Library for this item

ISBN: 9780198526155


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