Please click here to see abstracts.

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Keynote Speakers
Professor Gareth Roberts
Some recent developments in scaling of Metropolis-Hastings Algorithms

Harvard Rue
Alternatives to MCMC based inference for spatial models

Eric Moulines
ODE methods for Markov chain stability with applications to MCMC

Christophe Adrieu
On the psuedo-marginal Hastings-Metropolis algorithm

Samuel Kou
Equi-energy sampler: From statistical inference to statistical mechanics to protein folding

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Invited Session 1
Jeffrey Rosenthal
Adaptive MCMC: A Java Applet's Perspective

Mylene Bedard
Optimal acceptance rates for Metropolis algorithms: moving beyond 0.234

 

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Invited Session 2
Nial Friel
Recursive computing and simulation-free inference for Markov random fields

Merrilee Hurn
MCMC for estimating galaxy redshift

Mark Huber
Perfect simulation for continuous state spaces with the Randomness Recycler

Wilfrid Kendall
Perfect simulation: a survey

 

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Invited Session 3
Gersende Fort
Criteria for subgeometric ergodicity of strong Markov processes

Peter Green
Branching processes Monte Carlo

Omiros Papaspiliopoulos
Stability of the Gibbs sampler of Bayesian hierarchical models

 

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Invited Session 4
Andrew Stuart
Sampling Conditional Diffusions

Jochen Voss
An MCMC Method for Sampling Diffusion Bridges

 

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Invited Session 5
David Stephens
MCMC for Levy Processes of Stochastic Volatility

Chris Holmes
MCMC methods for inferring ancestry within subpopulations undergoing genetic transfer

Sylvia Richardson
MCMC methods for Bayesian variable selection in cased where structured dependence among the covariates is present: application to gene expression data

Eleisa Heron
Parameter estimation for a stochastic model of a gene regulatory network

 

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Posters
Teresa Barata
Photo-identification of bottlenose dolphins using MCMC

Andrew Golightly
Bayesian inference for nonlinear diffusion models observed with error

Maria Kalli
Mixtures of Dirichlet Processes (MDP) and the Slice Sampler

Michalis Kolossiatis
Bayesian nonparametric modelling of spatial data

Theodore Kypraios
Robust MCMC algorithms for a stochastic epidemic model and a fully Bayesian Analysis of the 2001 Foot-And-Mouth Epidemic occurred in the UK

Demetris Lamnisos
Bayesian Variable selection in classification problems

Beatriz Penaloza
The Uncertainty of Binary Data Models

Volker Schmid
A non-parametric approach for PK models in DCE-MRI

Chris Sherlock
Optimal scaling for the Metropolis-Hastings random-walk on unimodel elliptically symmetric targets

Tristan Marshall
Perfect Simulation for parameters of a partially observed diffusion process

Bruno Casella
Partially Implicit Langevin Schemes with MCMC applications

Miguel Belmonte
Stochastic Conditional Duration model and Particle Filters