New Developments for Bayesian statistical models and computational methods.

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Bayesian methods of statistical analysis provide a flexible theory for addressing inference in the presence of uncertainty. Consequently Bayesian methods have enabled scientific discovery in areas characterised as complex systems where new developments in modelling and computational methods have been crucial. Significant barriers to further success involve challenges in formulating and validating models, dealing with large data sets, and developing efficient computational methods. The principal aim of this project is to develop new Bayesian modelling and computational methodology which address these challenges with broad application.