event
Thursday 05 Jul 2012: Conjugate and Conditional Conjugate Bayesian Analysis of Discrete Graphical Models of Marginal Independence
Claudia Tarantola - Department of Economics and Business Sciences, University of Pavia, Italy
Portland Square C4, Plymouth University 15:00-16:00
We present a conjugate and conditional conjugate Bayesian analysis of marginal log-linear models with a bi-directed graph representation, exploiting the relationship between bi-
directed graphs and directed acyclic graphs or DAGs. A bi-directed graph can always be represented via a Markov equivalent DAG with the same vertex set or with the introduction
of further vertices, representing latent or hidden variables. The representation in terms of a DAG allows us to use efficient prior distributions based on product of Dirichlet priors.
The marginal likelihood of graphs without a direct representation in terms of a DAG is computed using the Chib approximation method. The posterior distribution of the
marginal log-linear parameters is obtained via Monte Carlo simulation The methodology is illustrated with reference to a three and a four way contingency table.
Joint work with Ioannis Ntzoufras, Department of Statistics, Athens University of Economics and Business, Greece.
