Workshop on Bayesian Inference for Latent Gaussian Models with Applications


Organized by Reinhard Furrer - Institute of Mathematics and Leonhard Held - Institute for Social and Preventive Medicine.
The workshop is sponsered by the University of Zurich.

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.

Confirmed invited speakers are:

  • Gonzalo García-Donato (UCLM, Spain)
  • Objective priors and search strategies in large variable selection problems
  • Sylvia Frühwirth-Schnatter (JKU, Austria)
  • Bayesian variable selection and model identification through sparsity priors
  • Alan Gelfand (Duke, USA)
  • Point pattern modeling for degraded presence-only data over large regions
  • Chris Holmes (Oxford, UK)
  • Computational strategies for Bayesian logistic regression analysis in genetic association studies within related populations
  • Finn Lindgren (NTNU, Norway)
  • How to avoid covariance functions, kernels, and dense lattices
  • Christopher Paciorek (Harvard, USA)
  • A unified approach to spatial modeling using Markov random fields?
  • Christian P. Robert (Paris, France)
  • ABC methods for Bayesian model choice
  • Håvard Rue (NTNU, Norway)
  • INLA: Past, Present & Future
  • Stephan Sain (NCAR, USA)
  • Statistical analysis of regional climate model ensembles: NARCCAP case studies

    On Wednesday morning, Håvard Rue will present a tutorial about INLA.

    Abstract submission for contributed talks and poster presentations is now closed.