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Peter Green, Nils Hjort, Sylvia Richardson: Introduction; 1 Steffen Lauritzen: Some modern applications of graphical models; Nanny Wermuth: Analysing social science data with graphical Markov models; Julia Mortera: 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 S. Richardson and Peter Sprites: 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 filtering 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 models 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-temporal 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

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