The Oxford Handbook of Applied Bayesian Analysis

by Anthony O' Hagan (Editor), Mike West (Editor)

Overview

Bayesian analysis has developed rapidly in applications in the last two decades and research in Bayesian methods remains dynamic and fast-growing. Dramatic advances in modelling concepts and computational technologies now enable routine application of Bayesian analysis using increasingly realistic stochastic models, and this drives the adoption of Bayesian approaches in many areas of science, technology, commerce, and industry. This Handbook explores contemporary Bayesian analysis across a variety of application areas. Chapters written by leading exponents of applied Bayesian analysis showcase the scientific ease and natural application of Bayesian modelling, and present solutions to real, engaging, societally important and demanding problems. The chapters are grouped into five general areas: Biomedical&Health Sciences; Industry, Economics&Finance; Environment&Ecology; Policy, Political&Social Sciences; and Natural&Engineering Sciences, and Appendix material in each touches on key concepts, models, and techniques of the chapter that are also of broader pedagogic and applied interest.

Product Details

ISBN-13:	9780191613890
Publisher:	OUP Oxford
Publication date:	03/18/2010
Series:	Oxford Handbooks
Sold by:	Barnes & Noble
Format:	eBook
File size:	51 MB
Note:	This product may take a few minutes to download.

About the Author

Anthony 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.

Table of Contents

PrefacePart I - Biomedical & Health Sciences1. Flexible Bayes Regression of Epidemiologic Data, David Dunson2. Bayesian Modelling for Matching and Alignment of Biomolecules, Peter Green, Kanti Mardia, Vysaul Nyirongo & Yann Ruffieux3. Bayesian Approaches to Aspects of the Vioxx Trials: Non-ignorable Dropout and Sequential Meta-Analysis, Jerry Cheng & David Madigan4. Sensitivity Analysis in Microbial Risk Assessment: Vero-cytotoxigenic E.coli O157 in Farm-Pasteurised Milk, Jeremy Oakley & Helen Clough5. Mapping Malaria in the Amazon Rain Forest: a Spatio-Temporal Mixture Model, Alexandra Schmidt, Jennifer Hoeting, João Batista Pereira & Pedro Paulo Vieira6. Trans-Study Projection of Genomic Biomarkers in Analysis of Oncogene Deregulation and Breast Cancer, Dan Merl, Joseph Lucas, Joseph Nevins, Haige Shenz & Mike West7. Linking Systems Biology Models to Data: a Stochastic Kinetic Model of p53 Oscillations, D. A. Henderson, R.J. Boys, C.J. Proctor & D.J. WilkinsonPart II - Industry, Economics & Finance8. Bayesian Analysis and Decisions in Nuclear Power Plant Maintenance, Elmira Popova, David Morton, Paul Damien & Tim Hanson9. Bayes Linear Uncertainty Analysis for Oil Reservoirs Based on Multiscale Computer Experiments, Jonathan Cumming & Michael Goldstein10. Bayesian Modelling of Train Doors Reliability, Antonio Pievatolo & Fabrizio Ruggeri11. Analysis of Economic Data With Multiscale Spatio-temporal Models, Marco Ferreira, Adelmo Bertoldey & Scott Holan12. Extracting S&P500 and NASDAQ Volatility: The Credit Crisis of 2007-2008, Hedibert Lopes & Nicholas Polson13. Futures Markets, Bayesian Forecasting, and Risk Modeling, José Mario Quintana, Carlos Carvalho, James Scott & Thomas Costigliola14. The New Macroeconometrics: A Bayesian Approach, Jesús Fernández-Villaverde, Pablo Guerrón-Quintana & Juan Rubio-RamírezPart III - Environment & Ecology15. Assessing The Probability of Rare Climate Events, Peter Challenor, Doug McNeall & James Gattiker16. Models for Demography of Plant Populations, James Clark, Dave Bell, Michael Dietze, Michelle Hersh, Ines Ibanez, Shannon LaDeau, Sean McMahon, Jessica Metcalf, Emily Moran, Luke Pangle & Mike Wolosin17. Combining Monitoring Data and Computer Model Output in Assessing Environmental Exposure, Alan Gelfand & Sujit K. Sahu18. Indirect Elicitation From Ecological Experts: From Methods and Software to Habitat Modelling and Rock-Wallabies, Samantha Low Choy, Justine Murray, Allan James & Kerrie Mengersen19. Characterizing the Uncertainty of Climate Change Projections Using Hierarchical Models, Claudia Tebaldi & Richard SmithPart IV - Policy, Political & Social Sciences20. Volatility in Prediction Markets: A Measure of Information Flow in Political Campaigns, Carlos Carvalho & Jill Rickershauser21. Paternity Testing Allowing for Uncertain Mutation Rates, Philip Dawid, Julia Mortera & Paola Vicard22. Bayesian Analysis in Item Response Theory Applied to a Large-scale Educational Assessment, Dani Gamerman, Tufi Soňares & Flávio Gonçalves23. Sequential Multi-location Auditing and the New York Food Stamps Program, Karl Heiner, Marc Kennedy & Anthony O'Hagan24. Bayesian Causal Inference: Approaches to Estimating the Effect of Treating Hospital Type on Cancer Survival in Sweden Using Principal Stratification, Donald Rubin, Xiaoqin Wang, Li Yin & Elizabeth ZellPart V - Natural & Engineering Sciences25. Bayesian Statistical Methods for Audio and Music Processing, A. Taylan Cemgil, Simon Godsill, Paul Peeling & Nick Whiteley26. Combining Simulations and Physical Observations to Estimate Cosmological Parameters, Dave Higdon, Katrin Heitmann, Charles Nakhleh & Salman Habib27. Probabilistic Grammars and Hierarchical Dirichlet Processes, Percy Liang, Michael Jordan & Dan Klein28. Designing and Analyzing a Circuit Device Experiment Using Treed Gaussian Processes, Herbert Lee, Matthew Taddy, Robert Gramacy & Genetha Gray29. Multi-state Models for Mental Fatigue, Raquel PradoIndex