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Speaker: Prof. Antonietta Mira Location: Join the webinar: https://us02web.zoom.us/j/87487369698?pwd=TnNaQmhoOUFxMXY5QUU0R1I0Z2xCdz09

Introduction to Approximate Bayesian Computation

The goal of statistical inference is to draw conclusions about properties of a population given a finite observed sample. This typically proceeds by first specifying a parametric statistical model (that identifies a likelihood function) for the data generating process which is indexed by parameters that need to be calibrated (estimated). There is always a trade-off between model simplicity / inferencial effort / prediction power. [more]
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