Next month, Kerrie Mengersen (QUT, Brisbane, Australia, and visiting us at CREST and Paris-Dauphine this coming May) will give a PhD course at CREST on the theme of applied Bayesian statistical modelling.
Here is her abstract:
Bayesian hierarchical models are now widely used in addressing a rich variety of real-world problems. In this course, we will examine some common models and the associated computational methods used to solve these problems, with a focus on environmental and health applications.
Two types of hierarchical models will be considered, namely mixture models and spatial models. Computational methods will cover Markov chain Monte Carlo, Variational Bayes and Approximate Bayesian Computation.
Participants will have the opportunity to implement these approaches using a number of datasets taken from real case studies, including the analysis of digital images from animals and satellites, and disease mapping for medicine and biosecurity.
The classes will take place at ENSAE, Paris, on May 3, 10 (14:00, Amphi 2), 14, and 21 (11:00, Room S8). (The course is open to everyone and free of charge, but registrations are requested, please contact Nadine Guedj.)