Peter Green, Nils Hjort, Sylvia Richardson: Introduction 1. Steffen Lauritzen: Some modern applications of graphical models Nanny Wermuth: Analysing social science data with graphical Markoc models Julia Moreta: Analysis of DNA mixtures using Bayesian networks 2. Philip Dawid: Causal inference using influence diagrams: the problem of partial compliance Elja Arjas: Commentary: causality and statistics James Robins: Semantics of causal DAG models and the identification of direct and indirect effects 3. Thomas Richardson: Causal inference via ancestral graph models Milan Studeny: Other approaches to description of conditional independence structures Jan Koster: On ancestral graph Markov models 4. Rainer Dahlhaus and Michael Eichler: Causality and graphical models in times series analysis Vanessa Didelez: Graphical models for stochastic processes Hans Kunsch: Discussion of "Causality and graphical models in times series analysis" 5. Gareth Roberts: Linking theory and practice of MCMC Christian Robert: Advances in MCMC: a discussion Arnoldo Frigessi: On some current research in MCMC 6. Peter Green: Trans-dimensional Markov chain Monte Carlo Simon Godsill: Proposal densities and product space methods Juha Heikkinen: Trans-dimensional Bayesian nonparametrics with spatial point processes 7. Carlo Berzuini and Walter Gilks: Particle flitering methods for dynamic and static Bayesian problems Geir Storvik: Some further topics on Monte Carlo methods for dynamic Bayesian problems Peter Clifford: General principles in sequential Monte Carlo methods 8.

Sylvia Richardson: Spatial modeals in epidemiological applications Leonhard Knorr-Held: Some remarks on Gaussian Markov random field models Jesper Moller: A compariosn of spatial point process models in epidemiological applications 9. Antti Penttinen, Fabio Divino and Anne Riiali: Spatial hierarchical Bayesian modeld in ecological applications Julian Besag: Likelihood analysis of binary data in space and time Alexandro Mello Schmidt: Some further aspects of spatio-temproal modelling 10. Merrilee Hurn; Oddvar Husby and Havard Rue: Advances in Bayesian image analysis M van Lieshout: Probabilistic image modelling Alain Trubuil: Prospects in Bayesian image analysis 11. Niels Becker and Sergey Utev: Preventing epidemics in heterogeneous environments Philip O'Neill: MCMC methods for stochastic epidemic models Kari Auranen: Towards Bayesian inference in epidemic models 12. Simon Heath: Genetic linkage analysis using Markov chain Monte Carlo techniques Nuala Sheehan and Daniel Sorensen: Graphical models for mapping continuous traits David Stephens: Statistical approaches to Genetic Mapping 13. R C Griffiths and Simon Tavare: The genealogy of neutral mutation Gunter Weiss: Linked versus unlinked DNA data - a comparison based on ancestral inference Carsten Wiuf: The age of a rare mutation 14. Anthony O'Hagan: HSSS model criticism M J Bayarri: What 'base' distribution for model criticism? Alan Gelfand: Some comments on model criticism 15. Nils Hjort: Topics in nonparametric Bayesian statistics Aad van der Vaart: Asymptotics of Nonparametirc Posteriors Sonia Petrone: A predictive point of view on Bayesian nonparametrics.