Bayesian Graphical Modelling: A Case-Study in Monitoring Health Outcomes
David J. Spiegelhalter · Journal of the Royal Statistical Society Series C (Applied Statistics) · 1998
SUMMARY Bayesian graphical modelling represents the synthesis of several recent developments in applied complex modelling. After describing a moderately challenging real example, we show how graphical models and Markov chain Monte Carlo methods naturally provide a direct path between model specification and the computational means of making inferences on that model. These ideas are illustrated with a range of modelling issues related to our example. An appendix discusses the BUGS software.