The Oxford Handbook of Applied Bayesian Analysis

• Preface


• Part I - Biomedical and Health Sciences


• 1: David Dunson: Flexible Bayes Regression of Epidemiologic Data


• 2: Peter Green, Kanti Mardia, Vysaul Nyirongo and Yann Ruffieux: Bayesian Modelling for Matching and Alignment of Biomolecules


• 3: Jerry Cheng and David Madigan: Bayesian Approaches to Aspects of the Vioxx Trials: Non-ignorable Dropout and Sequential Meta-Analysis


• 4: Jeremy Oakley and Helen Clough: Sensitivity Analysis in Microbial Risk Assessment: Vero-cytotoxigenic E.coli O157 in Farm-Pasteurised Milk


• 5: Alexandra Schmidt, Jennifer Hoeting, João Batista Pereira and Pedro Paulo Vieira: Mapping Malaria in the Amazon Rain Forest: a Spatio-Temporal Mixture Model


• 6: Dan Merl, Joseph Lucas, Joseph Nevins, Haige Shenz and Mike West: Trans-Study Projection of Genomic Biomarkers in Analysis of Oncogene Deregulation and Breast Cancer


• 7: D. A. Henderson, R.J. Boys, C.J. Proctor and D.J. Wilkinson: Linking Systems Biology Models to Data: a Stochastic Kinetic Model of p53 Oscillations


• Part II - Industry, Economics and Finance


• 8: Elmira Popova, David Morton, Paul Damien and Tim Hanson: Bayesian Analysis and Decisions in Nuclear Power Plant Maintenance


• 9: Jonathan Cumming and Michael Goldstein: Bayes Linear Uncertainty Analysis for Oil Reservoirs Based on Multiscale Computer Experiments


• 10: Antonio Pievatolo and Fabrizio Ruggeri: Bayesian Modelling of Train Doors Reliability


• 11: Marco Ferreira, Adelmo Bertoldey and Scott Holan: Analysis of Economic Data With Multiscale Spatio-temporal Models


• 12: Hedibert Lopes and Nicholas Polson: Extracting SandP500 and NASDAQ Volatility: The Credit Crisis of 2007-2008


• 13: José Mario Quintana, Carlos Carvalho, James Scott and Thomas Costigliola: Futures Markets, Bayesian Forecasting, and Risk Modeling

Tony O'Hagan is internationally recognized for his research in the methodology and applications of Bayesian statistics. Following BSc and PhD degrees from the University of London, he taught at the Universities of Dundee and Warwick before becoming a full professor at the University of Nottingham and then the University of Sheffield. He has also spent two years working in the electricity industry. He has substantial applied expertise from applications in many fields, including engineering, health, environmental science and finance.

Mike West is an international research and educational leader in statistical science whose areas of expertise span a range of areas in Bayesian statistical modelling and computational statistics, and inter-disciplinary applications in science, biomedicine, finance and other areas. West was a faculty member at the leading Bayesian centre at Warwick University UK in the 1980s, and led the development of one of the main centres worldwide - at Duke
University -- during the 1990s and into the Bayesian 21st century. As distinguished professor of statistical science at Duke University, West is broadly engaged in national and international professional activities, his research continues to emphasise Bayesian methodology development and applications of complex stochastic modelling, while his major professional focus remains the engagement and mentoring of future statistical scientists.