Mike West, Duke University  

Mike West
The Arts & Sciences Distinguished Professor of Statistics & Decision Sciences
Department of Statistical Science, Duke University

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The Oxford Handbook of
Applied Bayesian Analysis

Tony O'Hagan and Mike West (eds.)
Oxford University Press

ISBN: 978-0-19-954890-3

OUP UK and/or OUP US


The Handbook of Applied Bayesian Analysis is a showcase of contemporary Bayesian analysis in important and challenging applied problems, bringing together detailed studies by leading researchers and practitioners in interdisciplinary Bayesian analysis. Each chapter presents authoritative discussions of currently topical application areas together with key aspects of Bayesian analysis in these areas, and takes the reader to the cutting edge of research in that topic.

The Handbook is of broad interest to researchers and expert practitioners, as well as to advanced students in statistical science and related disciplines. The important and challenging studies represented across a diverse ranges of applications areas, involving cutting-edge statistical thinking and a broad array of Bayesian model-based and computational methodologies, will enthuse new researchers and non-statistical readers; they exemplify and will promote cross-fertilisation in advanced statistical thinking across multiple application areas. The Handbook is a reference resource for researchers across these fields as well as within statistical science, and for broad use in support of education and teaching, as well as in disciplinary and inter-disciplinary research.


  • Preface
    Tony O'Hagan & Mike West

  • Part I: Biomedical and Health Science
    • Flexible Bayes regression of epidemiologic data
      David B. Dunson
    • Bayesian modelling for matching and alignment of biomolecules
      Peter J. Green, Kanti V. Mardia, Vysaul B. Nyirongo and Yann Ruffieux
    • Bayesian approaches to aspects of the Vioxx trials: Non-ignorable dropout and sequential meta-analysis
      Jerry Cheng and David Madigan
    • Sensitivity analysis in microbial risk assessment: Vero-cytotoxigenic E. coli in farm-pasteurised milk
      Jeremy E. Oakley and Helen E. Clough
    • Mapping malaria in the Amazon rain forest: A spatio-temporal mixture model
      Alexandra M. Schmidt, Jennifer A. Hoeting, João Batista M. Pereira and Pedro Paulo Vieira
    • Trans-study projection of genomic biomarkers in analysis of oncogene deregulation and breast cancer
      Dan Merl, Joseph E. Lucas, Joseph R. Nevins, Haige Shen and Mike West
    • Linking systems biology models to data: A stochastic kinetic model of p53 oscillations
      D.A. Henderson, R.J. Boys, C.J. Proctor and D.J. Wilkinson
    • Paternity testing allowing for uncertain mutation rates
      A. Philip Dawid, Julia Mortera and Paola Vicard

  • Part II: Industry, Economics and Finance
    • Bayesian analysis and decisions in nuclear power plant maintenance
      Elmira Popova, David Morton, Paul Damien and Tim Hanson
    • Bayes linear uncertainty analysis for oil reservoirs based on multiscale computer experiments
      Jonathan Cumming and Michael Goldstein
    • Bayesian modelling of train door reliability
      Antonio Pievatolo and Fabrizio Ruggeri
    • Analysis of economic data with multiscale spatio-temporal models
      Marco A.R. Ferreira, Adelmo I. Bertolde and Scott H. Holan
    • Extracting S&P500 and NASDAQ volatility: The credit crisis of 2007-2008
      Hedibert F. Lopes and Nicholas G. Polson
    • Futures markets, Bayesian forecasting and risk modelling
      José Mario Quintana, Carlos M. Carvalho, James Scott and Thomas Costigliola
    • The new macroeconomics: A Bayesian approach
      Jesus Fernandez-Villaverde, Pablo Guerron-Quintana and Juan F. Rubio-Ramirez

  • Part III: Environment and Ecology
    • Assessing the probability of rare climate events
      Peter Challenor, Doug McNeal and James Gattiker
    • Models of demography of plant populations
      James S. Clark, Dave Bell, Michael Dietze, Michelle Hersh, Ines Ibanez, Shannon L. La Deau, Sean McMahon, Jessica Metclaf, Emily Moran, Luke Pangle and Mike Wolosin
    • Combining monitoring data and computer model output in assessing environmental exposure
      Alan E. Gelfand and Sujit K. Sahu
    • Indirect elicitation from ecological experts: From methods and software to habitat modelling and rock-wallabies
      Samantha Low Choy, Justine Murray, Allan Jones and Kerrie Mengersen
    • Characterizing the uncertainty of climate change projections using hierarchical models
      Claudia Tebaldi and Richard L. Smith

  • Part IV: Policy, Political and Social Sciences
    • Volatility in prediction markets: A measure of information flow in political campaigns
      Carlos M. Carvalho and Jill Rickershauser
    • Bayesian analysis in item response theory applied to a large-scale educational assessment
      Dani Gamerman, Tufi M. Soares and Flávio B. Gonçalves
    • Sequential multi-location auditing and the New York Food Stamps Program
      Karl Heiner, Marc C. Kennedy and Anthony O'Hagan
    • Bayesian causal inference: Approaches to estimating the effect of treating hospital type on cancer survival in Sweden using principal stratification
      Donald B. Rubin, Xiaoqin Wang, Li Yin and Elizabeth R. Zell

  • Part V: Natural and Engineering Sciences
    • Bayesian statistical methods for audio and music processing
      A. Taylan Cemgil, Simon J. Godsill, Paul Peeling and Nick Whitely
    • Combining simulations and physical observation to estimate cosmological parameters
      Dave Higdon, Katrin Heitmann, Charles Nakhleh and Salman Habib
    • Probabilistic grammars and hierarchical Dirichlet processes
      Percy Liang, Michael I. Jordan and Dan Klein
    • Designing and analysing a circuit device experiment using treed Gaussian processes
      Herbert K.H. Lee, Matthew Taddy, Robert B. Gramacy and Genetha A. Gray
    • Multi-state models for mental fatigue
      Raquel Prado