REMINDER!
Royal Statistical Society
Statistical Computing Section Meeting
Wednesday 20 January, 2.00 - 5.00pm at the RSS
(Tea 3:30pm)
Gibbs sampling, WinBUGS and perfect simulation
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Speakers
KAREN VINES (Open University)
DAVID SPIEGELHALTER (MRC Biostatistics Unit Cambridge)
ANDREW THOMAS (Imperial College London)
PETER GREEN (University of Bristol)
Programme
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2.00pm Karen Vines Introduction to MCMC and graphical models
2.45pm David Spiegelhalter & WinBUGS
Andrew Thomas
3.30pm Tea
4.00pm Peter Green Perfect simulation, and its possibilities in
Bayesian statistics
Synopses
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KAREN VINES (Open University)
Introduction to MCMC and graphical models
This talk aims to provide a basic overview of Markov chain
Monte Carlo (MCMC) techniques for the novice practitioner.
Starting from the use of graphical models to identify
exploitable conditional independence relationships and going
through to interpretation of the output, we will cover
issues that can arise in any analysis.
DAVID SPIEGELHALTER (MRC Biostatistics Unit Cambridge) and
ANDREW THOMAS (Imperial College London)
WinBUGS
WinBUGS performs MCMC analysis on Bayesian graphical models.
We shall discuss the philosophy behind the program and
demonstrate some recent developments. WinBUGS is freely available
from http://www.mrc-bsu.cam.ac.uk/bugs.
PETER GREEN (University of Bristol)
Perfect simulation, and its possibilities in Bayesian statistics
With the ultimate objective of Bayesian MCMC with guaranteed
convergence, the purpose of this talk is to describe recent efforts
to construct exact sampling methods for continuous-state Markov
chains. We will consider whether application of such methods could
become sufficiently convenient that they could become the basis for
routine Bayesian computation in the foreseeable future. This is joint
work with Duncan Murdoch.
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Suzanne Evans
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