Bayesian Inference for Latent Gaussian Models
Latent Gaussian models have numerous applications, for example in spatial and spatio-temporal epidemiology and climate modelling. This workshop brings together researchers who develop and apply Bayesian inference in this broad model class. One methodological focus is on model computation, using either classical MCMC techniques or more recent deterministic approaches such as integrated nested Laplace approximations (INLA). A second theme of the workshop is model uncertainty, ranging from model criticism to model selection and model averaging. Havard Rue will give an INLA tutorial on the first day. Further confirmed invited speakers are Renato Assuncao, Gonzalo Garcia-Donato, Sylvia Frühwirth-Schnatter, Alan Gelfand, Chris Holmes, Finn Lindgren, Douglas Nychka, Christopher Paciorek and Stephen Sain. Contributed talks and a poster session complete the four-day program.