Highly Structured Stochastic Systems

Peter J. GreenProfessor of Statistics, University of BristolNils Lid HjortProfessor of mathematical statistics, University of OsloSylvia RichardsonProfessor of Biostatistics, Imperial College

• Introduction ; 1. Some modern applications of graphical models ; Analysing social science data with graphical Markov models ; Analysis of DNA mixtures using Bayesian networks ; 2. Causal inference using influence diagrams: the problem of partial compliance ; Commentary: causality and statistics ; Semantics of causal DAG models and the identification of direct and indirect effects ; 3. Causal inference via ancestral graph models ; Other approaches to description of conditional independence structures ; On ancestral graph Markov models ; 4. Causality and graphical models in times series analysis ; Graphical models for stochastic processes ; Discussion of "Causality and graphical models in times series analysis" ; 5. Linking theory and practice of MCMC ; Advances in MCMC: a discussion ; On some current research in MCMC ; 6. Trans-dimensional Markov chain Monte Carlo ; Proposal densities and product space methods ; Trans-dimensional Bayesian nonparametrics with spatial point processes ; 7. Particle filtering methods for dynamic and static Bayesian problems ; Some further topics on Monte Carlo methods for dynamic Bayesian problems ; General principles in sequential Monte Carlo methods ; 8. Spatial models in epidemiological applications ; Some remarks on Gaussian Markov random field models ; A compariosn of spatial point process models in epidemiological applications ; 9. Spatial hierarchical Bayesian modeld in ecological applications ; Likelihood analysis of binary data in space and time ; Some further aspects of spatio-temporal modelling ; 10. Advances in Bayesian image analysis ; Probabilistic image modelling ; Prospects in Bayesian image analysis ; 11. Preventing epidemics in heterogeneous environments ; MCMC methods for stochastic epidemic models ; Towards Bayesian inference in epidemic models ; 12. Genetic linkage analysis using Markov chain Monte Carlo techniques ; Graphical models for mapping continuous traits ; Statistical approaches to Genetic Mapping ; 13. The genealogy of neutral mutation ; Linked versus unlinked DNA data - a comparison based on ancestral inference ; The age of a rare mutation ; 14. HSSS model criticism ; What 'base' distribution for model criticism? ; Some comments on model criticism ; 15. Topics in nonparametric Bayesian statistics ; Asymptotics of Nonparametirc Posteriors ; A predictive point of view on Bayesian nonparametrics