Jonathan J. Forster

Learn More
We consider how to compare different conditional independence specifications for ordinal categorical data, by calculating a posterior distribution over classes of graphical models. The approach is based on the multivariate ordinal probit model (Chib and Greenberg, 1998) where the data are considered to have arisen as truncated multivari-ate normal random(More)
A default strategy for fully Bayesian model determination for GLMMs is considered which addresses the two key issues of default prior specification and computation. In particular, the concept of unit information priors is extended to the parameters of a GLMM. A combination of MCMC and Laplace approximations is used to compute approximations to the posterior(More)
  • 1