Spatiotemporal Modelling

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Carefully modelling spatiotemporal data vital in fields as diverse as ecology, epidemiology, and fisheries science. As the size of datasets increases, so does the complexity of the associated statistical models. Dr. Simpson will develop improved Bayesian modelling pipelines to deal with the spatiotemporal models of real-world data. The effort spans issues of model specification, posterior computation, model checking, visualisation, and interpretation of results. The advances will be implemented in the popular R-INLA and Stan software packages, and are expected to have an impact in a number of areas of applied scientific research.