The Oxford Handbook Of Applied Bayesian Analysis

Author : Anthony O' Hagan,Mike West
Publisher : OUP Oxford
Page : 924 pages
File Size : 52,6 Mb
Release : 2010-03-18
Category : Mathematics
ISBN : 9780191613890

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The Oxford Handbook of Applied Bayesian Analysis by Anthony O' Hagan,Mike West Pdf

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.

Author : Herman van Dijk
Publisher : Oxford University Press
Page : 571 pages
File Size : 48,5 Mb
Release : 2011-09-29
Category : Business & Economics
ISBN : 9780199559084

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The Oxford Handbook of Bayesian Econometrics by Herman van Dijk Pdf

A broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing.

Author : Anthony O' Hagan,Mike West
Publisher : OUP Oxford
Page : 928 pages
File Size : 48,8 Mb
Release : 2010-03-18
Category : Mathematics
ISBN : 9780191582820

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The Oxford Handbook of Applied Bayesian Analysis by Anthony O' Hagan,Mike West Pdf

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.

Author : Mary Kathryn Cowles
Publisher : Springer Science & Business Media
Page : 238 pages
File Size : 46,5 Mb
Release : 2013-01-04
Category : Mathematics
ISBN : 9781461456964

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Applied Bayesian Statistics by Mary Kathryn Cowles Pdf

This book is based on over a dozen years teaching a Bayesian Statistics course. The material presented here has been used by students of different levels and disciplines, including advanced undergraduates studying Mathematics and Statistics and students in graduate programs in Statistics, Biostatistics, Engineering, Economics, Marketing, Pharmacy, and Psychology. The goal of the book is to impart the basics of designing and carrying out Bayesian analyses, and interpreting and communicating the results. In addition, readers will learn to use the predominant software for Bayesian model-fitting, R and OpenBUGS. The practical approach this book takes will help students of all levels to build understanding of the concepts and procedures required to answer real questions by performing Bayesian analysis of real data. Topics covered include comparing and contrasting Bayesian and classical methods, specifying hierarchical models, and assessing Markov chain Monte Carlo output. Kate Cowles taught Suzuki piano for many years before going to graduate school in Biostatistics. Her research areas are Bayesian and computational statistics, with application to environmental science. She is on the faculty of Statistics at The University of Iowa.

Author : Todd D. Little
Publisher : Oxford University Press
Page : 506 pages
File Size : 42,7 Mb
Release : 2013-01-15
Category : Psychology
ISBN : 9780199934881

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The Oxford Handbook of Quantitative Methods, Volume 1: Foundations by Todd D. Little Pdf

Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods is the complete tool box to deliver the most valid and generalizable answers to todays complex research questions. It is a one-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chapters associated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.

Author : Peter Congdon
Publisher : John Wiley & Sons
Page : 464 pages
File Size : 49,7 Mb
Release : 2014-06-25
Category : Mathematics
ISBN : 9781118895061

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Applied Bayesian Modelling by Peter Congdon Pdf

This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets. Following in the tradition of the successful first edition, this book aims to make a wide range of statistical modeling applications accessible using tested code that can be readily adapted to the reader's own applications. The second edition has been thoroughly reworked and updated to take account of advances in the field. A new set of worked examples is included. The novel aspect of the first edition was the coverage of statistical modeling using WinBUGS and OPENBUGS. This feature continues in the new edition along with examples using R to broaden appeal and for completeness of coverage.

Author : Springer
Publisher : Unknown
Page : 238 pages
File Size : 40,6 Mb
Release : 2013-01-01
Category : Electronic
ISBN : 1461456975

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Applied Bayesian Statistics by Springer Pdf

Author : Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
Publisher : CRC Press
Page : 677 pages
File Size : 46,7 Mb
Release : 2013-11-01
Category : Mathematics
ISBN : 9781439840955

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Bayesian Data Analysis, Third Edition by Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin Pdf

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Author : Todd D. Little
Publisher : Oxford Library of Psychology
Page : 536 pages
File Size : 42,9 Mb
Release : 2014
Category : Psychology
ISBN : 9780199370153

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The Oxford Handbook of Quantitative Methods by Todd D. Little Pdf

This two-volume handbook on current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences covers philosophical and ethical issues, theory construction, model building and types of models, survey and experiment design, measurement issues, observational methods, statistical methods, types of analysis, types of data, and common research fallacies.

Author : Peter D. Congdon
Publisher : CRC Press
Page : 606 pages
File Size : 54,8 Mb
Release : 2010-05-19
Category : Mathematics
ISBN : 9781584887218

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Applied Bayesian Hierarchical Methods by Peter D. Congdon Pdf

The use of Markov chain Monte Carlo (MCMC) methods for estimating hierarchical models involves complex data structures and is often described as a revolutionary development. An intermediate-level treatment of Bayesian hierarchical models and their applications, Applied Bayesian Hierarchical Methods demonstrates the advantages of a Bayesian approach

Author : Janet M. Box-Steffensmeier,Henry E. Brady,David Collier
Publisher : Oxford Handbooks of Political
Page : 880 pages
File Size : 46,5 Mb
Release : 2008
Category : Philosophy
ISBN : 019928654X

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The Oxford Handbook of Political Methodology by Janet M. Box-Steffensmeier,Henry E. Brady,David Collier Pdf

The Oxford Handbooks of Political Science are the essential guide to the state of political science today. With engaging contributions from major international scholars The Oxford Handbook of Political Methodology provides the key point of reference for anyone working throughout the discipline.

Author : Paul Damien,Petros Dellaportas,Nicholas G. Polson,David A. Stephens
Publisher : OUP Oxford
Page : 720 pages
File Size : 47,9 Mb
Release : 2013-01-24
Category : Mathematics
ISBN : 9780191647000

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

The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and developments, and who may be looking for ideas that could spawn new research. Hence, the audience for this unique book would likely include academicians/practitioners, and could likely be required reading for undergraduate and graduate students in statistics, medicine, engineering, scientific computation, business, psychology, bio-informatics, computational physics, graphical models, neural networks, geosciences, and public policy. The book honours the contributions of Sir Adrian F. M. Smith, one of the seminal Bayesian researchers, with his papers on hierarchical models, sequential Monte Carlo, and Markov chain Monte Carlo and his mentoring of numerous graduate students -the chapters are authored by prominent statisticians influenced by him. Bayesian Theory and Applications should serve the dual purpose of a reference book, and a textbook in Bayesian Statistics.

Author : Alicia A. Johnson,Mies Q. Ott,Mine Dogucu
Publisher : Unknown
Page : 521 pages
File Size : 53,6 Mb
Release : 2022
Category : Bayesian statistical decision theory
ISBN : 1032191597

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Bayes Rules! by Alicia A. Johnson,Mies Q. Ott,Mine Dogucu Pdf

This book brings the power of modern Bayesian thinking, modeling, and computing to a broad audience. In particular, it is an ideal resource for advanced undergraduate Statistics students and practitioners with comparable experience. It empowers readers to weave Bayesian approaches into their everyday practice.

Author : Ben Lambert
Publisher : SAGE
Page : 744 pages
File Size : 50,5 Mb
Release : 2018-04-20
Category : Social Science
ISBN : 9781526418265

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A Student’s Guide to Bayesian Statistics by Ben Lambert Pdf

Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first student-focused introduction to Bayesian statistics. Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, student-friendly language to provide approachable instruction perfectly aimed at statistics and Bayesian newcomers. Through a logical structure that introduces and builds upon key concepts in a gradual way and slowly acclimatizes students to using R and Stan software, the book covers: An introduction to probability and Bayesian inference Understanding Bayes′ rule Nuts and bolts of Bayesian analytic methods Computational Bayes and real-world Bayesian analysis Regression analysis and hierarchical methods This unique guide will help students develop the statistical confidence and skills to put the Bayesian formula into practice, from the basic concepts of statistical inference to complex applications of analyses.

Author : Peter Congdon
Publisher : Wiley
Page : 478 pages
File Size : 52,8 Mb
Release : 2003-04-18
Category : Mathematics
ISBN : 0471486957

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Applied Bayesian Modelling by Peter Congdon Pdf

The use of Bayesian statistics has grown significantly in recent years, and will undoubtedly continue to do so. Applied Bayesian Modelling is the follow-up to the author’s best selling book, Bayesian Statistical Modelling, and focuses on the potential applications of Bayesian techniques in a wide range of important topics in the social and health sciences. The applications are illustrated through many real-life examples and software implementation in WINBUGS – a popular software package that offers a simplified and flexible approach to statistical modelling. The book gives detailed explanations for each example – explaining fully the choice of model for each particular problem. The book · Provides a broad and comprehensive account of applied Bayesian modelling. · Describes a variety of model assessment methods and the flexibility of Bayesian prior specifications. · Covers many application areas, including panel data models, structural equation and other multivariate structure models, spatial analysis, survival analysis and epidemiology. · Provides detailed worked examples in WINBUGS to illustrate the practical application of the techniques described. All WINBUGS programs are available from an ftp site. The book provides a good introduction to Bayesian modelling and data analysis for a wide range of people involved in applied statistical analysis, including researchers and students from statistics, and the health and social sciences. The wealth of examples makes this book an ideal reference for anyone involved in statistical modelling and analysis.