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Bayesian Theory and Applications$
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Paul Damien, Petros Dellaportas, Nicholas G. Polson, and David A. Stephens

Print publication date: 2013

Print ISBN-13: 9780199695607

Published to Oxford Scholarship Online: May 2013

DOI: 10.1093/acprof:oso/9780199695607.001.0001

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Introduction

Introduction

Chapter:
(p.xii) Introduction
Source:
Bayesian Theory and Applications
Author(s):

Paul Damien

Petros Dellaportas

Nicholas G. Polson

David A. Stephens

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199695607.003.0034

This introductory chapter begins by noting how the three key ideas in this volume — hierarchical models, Markov chain Monte Carlo, and sequential Monte Carlo — that have revolutionized Bayesian statistics are in large measure due to the contributions of Adrian Smith. These concepts are now ubiquitous wherever Bayesian models are used. In this volume, broad topic areas have been selected where these ideas come into play in a significant manner. While these topics are by no means exhaustive, they serve to illustrate the impact of Adrian's research on Bayesian statistics in the last four decades or so. An overview of the twelve parts of the book is then presented.

Keywords:   Bayesian statistics, hierarchical models, Markov chain Monte Carlo, sequential Monte Carlo, Adrian Smith

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