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The Oxford Handbook of Applied Bayesian Analysis
Edited by Anthony O' Hagan and Mike West
928 pages
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200 illustrations
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246x171mm
978-0-19-954890-3
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Hardback
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18 March 2010
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- Editors and contributors are world leaders in their fields
- Applications cover just about every topical area of science, technology, and commerce
- Applications are all in real, engaging, societally important, and demanding problems, and discuss basic aspects of the path to solution as well as "big picture" questions
- Captures the breadth and essence of applied Bayesian analysis in a clear, concise, single volume
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.Readership: This Handbook will be of interest and use to statisticians and quantitative researchers requiring a broad overview of the applications of Bayesian Statistics, or those interested in solutions to specific
problems. It will be a major reference source for students in a wide variety of fields and aims to inspire researchers to venture further into these exciting and challenging application areas.
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Edited by Anthony O' Hagan, University of Sheffield, UK, and Mike West, Duke University, USA Contributors:
Dave Bell; Adelmo Bertolde; R.J. Boys; Carlos Carvalho; Taylan Cemgil; Peter Challenor; Jerry Cheng; Jim Clark; Helen Clough; Thomas Costigliola; Jonathan Cumming; Paul Damien; Philip Dawid; Michael Dietze; David Dunson; Jesús Fernández-Villaverde; Marco Ferreira; Dani Gamerman; James Gattiker; Alan Gelfand; Simon Godsill; Michael Goldstein; Flávio Gonçalves; Robert Gramacy; Genetha Gray; Peter Green; Pablo Guerrón-Quintana; Salman Habib; Tim Hanson; Karl Heiner; Katrin Heitmann; D.A. Henderson; Michelle Hersh; David
Higdon; Jennifer Hoeting; Scott Holan; Ines Ibanez; Allan James; Michael Jordan; Marc Kennedy; Dan Klein; Shannon LaDeau; Herbert Lee; Percy Liang; Hedibert Lopes; Samantha Low Choy; Joe Lucas; David Madigan; Kanti Mardia; Sean McMahon; Doug McNeall; Kerrie Mengersen; Dan Merl; Jessica Metcalf; Emily Moran; Julia Mortera; Dave Morton; Justine Murray; Charlie Nakhleh; Joseph Nevins; Vysaul Nyirongo; Jeremy Oakley; Anthony O'Hagan; Luke Pangle; Paul Peeling; João Batista Pereira; Antonio Pievatolo; Nicholas Polson; Emira Popova; Raquel Prado; C.J. Proctor; Jose Quintana; Jill Rickershauser; Donald Rubin; Juan Rubio-Ramírez; Yann Ruffieux; Fabrizio Ruggeri; Sujit Sahu; Alexandra Schmidt; James Scott; Haige Shen; Richard Smith; Tufi Soares; Matt Taddy; Claudia Tebaldi; Paola Vicard; Pedro
Paulo Vieira; Xiaoqin Wang; Mike West; Nick Whiteley; Darren Wilkinson; Mike Wolosin; Li Yin; Elizabeth Zell
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Preface
Part I - Biomedical & Health Sciences
1: David Dunson: Flexible Bayes Regression of Epidemiologic Data
2: Peter Green, Kanti Mardia, Vysaul Nyirongo & Yann Ruffieux: Bayesian Modelling for Matching and Alignment of Biomolecules
3: Jerry Cheng & David Madigan: Bayesian Approaches to Aspects of the Vioxx Trials: Non-ignorable Dropout and Sequential Meta-Analysis
4: Jeremy Oakley & 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 & Pedro Paulo Vieira: Mapping Malaria in the Amazon Rain Forest: a Spatio-Temporal Mixture Model
6: Dan Merl, Joseph Lucas, Joseph Nevins, Haige Shenz & 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 & D.J. Wilkinson: Linking Systems Biology Models to Data: a Stochastic Kinetic Model of p53 Oscillations
Part II - Industry, Economics & Finance
8: Elmira Popova, David Morton, Paul Damien & Tim Hanson: Bayesian Analysis and Decisions in Nuclear Power Plant Maintenance
9: Jonathan Cumming & Michael Goldstein: Bayes Linear Uncertainty Analysis for Oil Reservoirs Based on Multiscale Computer Experiments
10: Antonio Pievatolo & Fabrizio Ruggeri: Bayesian Modelling of Train Doors Reliability
11: Marco Ferreira, Adelmo Bertoldey & Scott Holan: Analysis of Economic Data With Multiscale Spatio-temporal Models
12: Hedibert Lopes & Nicholas Polson: Extracting S&P500 and NASDAQ Volatility: The Credit Crisis of 2007-2008
13: José Mario Quintana, Carlos Carvalho, James Scott & Thomas Costigliola: Futures Markets, Bayesian Forecasting, and Risk Modeling
14: Jesús Fernández-Villaverde, Pablo Guerrón-Quintana & Juan Rubio-Ramírez: The New Macroeconometrics: A Bayesian Approach
Part III - Environment & Ecology
15: Peter Challenor, Doug McNeall & James Gattiker: Assessing The Probability of Rare Climate Events
16: James Clark, Dave Bell, Michael Dietze, Michelle Hersh, Ines Ibanez, Shannon LaDeau, Sean McMahon, Jessica Metcalf, Emily Moran, Luke Pangle & Mike Wolosin: Models for Demography of Plant Populations
17: Alan Gelfand & Sujit K. Sahu: Combining Monitoring Data and Computer Model Output in Assessing Environmental Exposure
18: Samantha Low Choy, Justine Murray, Allan James & Kerrie Mengersen: Indirect Elicitation From Ecological Experts: From Methods and Software to Habitat Modelling and Rock-Wallabies
19: Claudia Tebaldi & Richard Smith: Characterizing the Uncertainty of Climate Change Projections Using Hierarchical Models
Part IV - Policy, Political & Social Sciences
20: Carlos Carvalho & Jill Rickershauser: Volatility in Prediction Markets: A Measure of Information Flow in Political Campaigns
21: Philip Dawid, Julia Mortera & Paola Vicard: Paternity Testing Allowing for Uncertain Mutation Rates
22: Dani Gamerman, Tufi Soares & Flávio Gonçalves: Bayesian Analysis in Item Response Theory Applied to a Large-scale Educational Assessment
23: Karl Heiner, Marc Kennedy & Anthony O'Hagan: Sequential Multi-location Auditing and the New York Food Stamps Program
24: Donald Rubin, Xiaoqin Wang, Li Yin & Elizabeth Zell: Bayesian Causal Inference: Approaches to Estimating the Effect of Treating Hospital Type on Cancer Survival in Sweden Using Principal Stratification
Part V - Natural & Engineering Sciences
25: A. Taylan Cemgil, Simon Godsill, Paul Peeling & Nick Whiteley: Bayesian Statistical Methods for Audio and Music Processing
26: Dave Higdon, Katrin Heitmann, Charles Nakhleh & Salman Habib: Combining Simulations and Physical Observations to Estimate Cosmological Parameters
27: Percy Liang, Michael Jordan & Dan Klein: Probabilistic Grammars and Hierarchical Dirichlet Processes
28: Herbert Lee, Matthew Taddy, Robert Gramacy & Genetha Gray: Designing and Analyzing a Circuit Device Experiment Using Treed Gaussian Processes
29: Raquel Prado: Multi-state Models for Mental Fatigue
Index
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The specification in this catalogue, including without limitation price, format, extent, number of illustrations, and month of publication, was as accurate as possible at the time the catalogue was compiled. Occasionally, due to the nature of some contractual restrictions, we are unable to ship a specific product to a particular territory. Jacket images are provisional and liable to change before publication.
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