Sampling latent Gaussian models and hierarchical modelling
Speaker: Iain Murray (University of Edinburgh)
Date: Thu 7th April 2011
Location: Statistics Seminar Room- L550 Library building
Sometimes hyperparameters of hierarchical probabilistic models are not well-specified enough to be optimized. In some scientific applications inferring their posterior distribution is the objective of learning. Using a simple example, I explain why Markov chain Monte Carlo (MCMC) simulation can be difficult, and offer a solution for latent Gaussian models.
(This talk is part of the Statistics and Actuarial Science series.)