Mathematical Sciences: The Practice of Bayesian Inference

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The research will extend the range of models and problems to which Bayesian analysis can routinely be applied. The objectives of the research include development of theoretical foundations and applicable methods for integrating multiple sources of information, both prior and data-based. They also include providing the applied statistician with indications of robustness with respect to priors and model structure. Other objectives are the development of novel modeling techniques to extend the applicability of dynamic forecasting and survival analysis as well as continued development of numerical methods for the evaluation of integrals required in Bayesian analysis. Much of the research is based on the development of entirely new lines of attack made possible by recent advances in computing. Accordingly, closely integrated analytical and experimental tools will be applied.