In Bayesian statistics, two influential papers in the latter part of the 20th Century—reprinted in Volume III of Breakthroughs in Statistics, Springer-Verlag—were co-authored by Adrian Smith. These papers contain two central ideas in the theory and practice of modern Bayesian statistics, namely Hierarchical Models (Lindley and Smith, Journal of the Royal Statistical Society, Series B, 1972) and Markov chain Monte Carlo (Gelfand and Smith, Journal of the American Statistical Society, 1990). This conference will showcase many key advances that continue to be made, using these ideas, by many established and younger researchers.
Research
involving hierarchical models and MCMC continues to
grow at an astonishing rate, spanning a broad spectrum of topics in
medicine,
engineering, scientific computation, business, psychology,
bio-informatics,
computational physics, graphical models, neural networks, geosciences,
and
public policy. This explosion of Bayesian ideas is, in part, the result
of papers
authored or co-authored by Adrian Smith.
The attached
links on this site
provide details of Adrian’s contributions
Organizing Committee:
Paul Damien (USA)
Petros Dellaportas (Greece)
Jon Forster (England)
Nick Polson (USA)
Gareth Roberts (England)
David Stephens (Canada)
Jon Wakefield (USA)