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Data Science Seminar Date: Friday, 18 October 2024 Time: 2:00 - 3:00 PM Venue: NKN Hall Bayesian Modeling of Spatio Temporal Data with R Sujit K. Sahu University of Southampton. 18-10-24 Abstract Spatio-temporal data are now ubiquitous in many applied sciences such as atmospheric, biological, climate, demographic, economic, ecological, environmental, oceanic and political. These data are often collected for the primary purposes of making wide ranging inference and prediction. Ideally such inferential tasks should be approached through statistical modeling, which aids in estimation of uncertainties in all conclusions drawn from such data. Unified Bayesian modeling, implemented through user friendly software packages, provides a crucial key to unlocking the full power of these methods for solving challenging practical problems. In this talk I will present many modeling methodologies discussed in my recent book of the same title. The methods largely vary according to the nature of the data sets they are used to analyse. All of the methodologies are packaged inside an R package of the same name. The user-friendly package, allows the data analysts to experiment a multiplicity of methods and software packages to solve each problem, thereby giving them access to various appropriate, but competing, tools. In each of the examples the main task is to validate the models using out of sample predictions. The introductory nature of the talk, and that of the book, is intended to attract the beginner researchers who may not be experts in the underlying theory of statistical modeling methods and computation.
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