Frontiers Of Statistical Decision Making And Bayesian Analysis

Author : Ming-Hui Chen,Peter Müller,Dongchu Sun,Keying Ye,Dipak K. Dey
Publisher : Springer Science & Business Media
Page : 631 pages
File Size : 52,9 Mb
Release : 2010-07-24
Category : Mathematics
ISBN : 9781441969446

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Frontiers of Statistical Decision Making and Bayesian Analysis by Ming-Hui Chen,Peter Müller,Dongchu Sun,Keying Ye,Dipak K. Dey Pdf

Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers. This book provides a review of current research challenges and opportunities. While the book can not exhaustively cover all current research areas, it does include some exemplary discussion of most research frontiers. Topics include objective Bayesian inference, shrinkage estimation and other decision based estimation, model selection and testing, nonparametric Bayes, the interface of Bayesian and frequentist inference, data mining and machine learning, methods for categorical and spatio-temporal data analysis and posterior simulation methods. Several major application areas are covered: computer models, Bayesian clinical trial design, epidemiology, phylogenetics, bioinformatics, climate modeling and applications in political science, finance and marketing. As a review of current research in Bayesian analysis the book presents a balance between theory and applications. The lack of a clear demarcation between theoretical and applied research is a reflection of the highly interdisciplinary and often applied nature of research in Bayesian statistics. The book is intended as an update for researchers in Bayesian statistics, including non-statisticians who make use of Bayesian inference to address substantive research questions in other fields. It would also be useful for graduate students and research scholars in statistics or biostatistics who wish to acquaint themselves with current research frontiers.

Author : Ming-Hui Chen,Peter Müller,Dongchu Sun,Keying Ye,Dipak Dey
Publisher : Springer
Page : 631 pages
File Size : 47,6 Mb
Release : 2010-08-05
Category : Mathematics
ISBN : 1441969454

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Frontiers of Statistical Decision Making and Bayesian Analysis by Ming-Hui Chen,Peter Müller,Dongchu Sun,Keying Ye,Dipak Dey Pdf

Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers. This book provides a review of current research challenges and opportunities. While the book can not exhaustively cover all current research areas, it does include some exemplary discussion of most research frontiers. Topics include objective Bayesian inference, shrinkage estimation and other decision based estimation, model selection and testing, nonparametric Bayes, the interface of Bayesian and frequentist inference, data mining and machine learning, methods for categorical and spatio-temporal data analysis and posterior simulation methods. Several major application areas are covered: computer models, Bayesian clinical trial design, epidemiology, phylogenetics, bioinformatics, climate modeling and applications in political science, finance and marketing. As a review of current research in Bayesian analysis the book presents a balance between theory and applications. The lack of a clear demarcation between theoretical and applied research is a reflection of the highly interdisciplinary and often applied nature of research in Bayesian statistics. The book is intended as an update for researchers in Bayesian statistics, including non-statisticians who make use of Bayesian inference to address substantive research questions in other fields. It would also be useful for graduate students and research scholars in statistics or biostatistics who wish to acquaint themselves with current research frontiers.

Author : James O. Berger
Publisher : Springer Science & Business Media
Page : 633 pages
File Size : 53,5 Mb
Release : 2013-03-14
Category : Mathematics
ISBN : 9781475742862

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Statistical Decision Theory and Bayesian Analysis by James O. Berger Pdf

In this new edition the author has added substantial material on Bayesian analysis, including lengthy new sections on such important topics as empirical and hierarchical Bayes analysis, Bayesian calculation, Bayesian communication, and group decision making. With these changes, the book can be used as a self-contained introduction to Bayesian analysis. In addition, much of the decision-theoretic portion of the text was updated, including new sections covering such modern topics as minimax multivariate (Stein) estimation.

Author : Shanti S. Gupta,James O. Berger
Publisher : Springer Science & Business Media
Page : 535 pages
File Size : 47,6 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9781461226185

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Statistical Decision Theory and Related Topics V by Shanti S. Gupta,James O. Berger Pdf

The Fifth Purdue International Symposium on Statistical Decision The was held at Purdue University during the period of ory and Related Topics June 14-19,1992. The symposium brought together many prominent leaders and younger researchers in statistical decision theory and related areas. The format of the Fifth Symposium was different from the previous symposia in that in addition to the 54 invited papers, there were 81 papers presented in contributed paper sessions. Of the 54 invited papers presented at the sym posium, 42 are collected in this volume. The papers are grouped into a total of six parts: Part 1 - Retrospective on Wald's Decision Theory and Sequential Analysis; Part 2 - Asymptotics and Nonparametrics; Part 3 - Bayesian Analysis; Part 4 - Decision Theory and Selection Procedures; Part 5 - Probability and Probabilistic Structures; and Part 6 - Sequential, Adaptive, and Filtering Problems. While many of the papers in the volume give the latest theoretical developments in these areas, a large number are either applied or creative review papers.

Author : James Berger
Publisher : Springer Science & Business Media
Page : 440 pages
File Size : 41,9 Mb
Release : 2013-04-17
Category : Mathematics
ISBN : 9781475717273

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Statistical Decision Theory by James Berger Pdf

Decision theory is generally taught in one of two very different ways. When of opti taught by theoretical statisticians, it tends to be presented as a set of mathematical techniques mality principles, together with a collection of various statistical procedures. When useful in establishing the optimality taught by applied decision theorists, it is usually a course in Bayesian analysis, showing how this one decision principle can be applied in various practical situations. The original goal I had in writing this book was to find some middle ground. I wanted a book which discussed the more theoretical ideas and techniques of decision theory, but in a manner that was constantly oriented towards solving statistical problems. In particular, it seemed crucial to include a discussion of when and why the various decision prin ciples should be used, and indeed why decision theory is needed at all. This original goal seemed indicated by my philosophical position at the time, which can best be described as basically neutral. I felt that no one approach to decision theory (or statistics) was clearly superior to the others, and so planned a rather low key and impartial presentation of the competing ideas. In the course of writing the book, however, I turned into a rabid Bayesian. There was no single cause for this conversion; just a gradual realization that things seemed to ultimately make sense only when looked at from the Bayesian viewpoint.

Author : Richard E. Barlow,C.A. Claroti,Fabio Spizzichino
Publisher : CRC Press
Page : 396 pages
File Size : 55,5 Mb
Release : 1993-09-01
Category : Business & Economics
ISBN : 0412534800

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Reliability and Decision Making by Richard E. Barlow,C.A. Claroti,Fabio Spizzichino Pdf

First published in 1993. Routledge is an imprint of Taylor & Francis, an informa company.

Author : Morris H. DeGroot,George E. P. Box,George C. Tiao,Howard Raiffa,Robert Schlaifer
Publisher : Wiley
Page : 0 pages
File Size : 43,7 Mb
Release : 2006-05-19
Category : Mathematics
ISBN : 047168788X

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Optimal Statistical Decision & Bayesian Inference in Statistical Analysis & Applied Statistical Decision Theory by Morris H. DeGroot,George E. P. Box,George C. Tiao,Howard Raiffa,Robert Schlaifer Pdf

Set that includes three works covering statistical decision theory and analysis The three books within this set are Optimal Statistical Decisions, Bayesian Inference in Statistical Analysis, and Applied Statistical Decision Theory. Optimal Statistical Decisions discusses the theory and methodology of decision-making in the field. The volume stands as a clear introduction to Bayesian statistical decision theory. A second book, Bayesian Inference in Statistical Analysis, examines the application and relevance of Bayes' theorem to problems that occur during scientific investigations, where inferences must be made regarding parameter values about which little is known. Key aspects of the Bayesian approach are discussed, including the choice of prior distribution, the problem of nuisance parameters, and the role of sufficient statistics. Applied Statistical Decision Theory covers the development of analytic techniques in the field of statistical decision theory. This classic book was first published in the 1960s.

Author : John Winsor Pratt,Howard Raiffa,Robert Schlaifer
Publisher : MIT Press
Page : 906 pages
File Size : 46,7 Mb
Release : 1995
Category : Business & Economics
ISBN : 0262161443

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Introduction to Statistical Decision Theory by John Winsor Pratt,Howard Raiffa,Robert Schlaifer Pdf

They then examine the Bernoulli, Poisson, and Normal (univariate and multivariate) data generating processes.

Author : S. Panchapakesan,N. Balakrishnan
Publisher : Springer Science & Business Media
Page : 478 pages
File Size : 53,5 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461223085

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Advances in Statistical Decision Theory and Applications by S. Panchapakesan,N. Balakrishnan Pdf

Shanti S. Gupta has made pioneering contributions to ranking and selection theory; in particular, to subset selection theory. His list of publications and the numerous citations his publications have received over the last forty years will amply testify to this fact. Besides ranking and selection, his interests include order statistics and reliability theory. The first editor's association with Shanti Gupta goes back to 1965 when he came to Purdue to do his Ph.D. He has the good fortune of being a student, a colleague and a long-standing collaborator of Shanti Gupta. The second editor's association with Shanti Gupta began in 1978 when he started his research in the area of order statistics. During the past twenty years, he has collaborated with Shanti Gupta on several publications. We both feel that our lives have been enriched by our association with him. He has indeed been a friend, philosopher and guide to us.

Author : Silvia Bacci,Bruno Chiandotto
Publisher : CRC Press
Page : 217 pages
File Size : 50,5 Mb
Release : 2019-07-11
Category : Mathematics
ISBN : 9781351621380

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Introduction to Statistical Decision Theory by Silvia Bacci,Bruno Chiandotto Pdf

Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision theory from a statistical perspective. It covers both traditional approaches, in terms of value theory and expected utility theory, and recent developments, in terms of causal inference. The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory. Features Covers approaches for making decisions under certainty, risk, and uncertainty Illustrates expected utility theory and its extensions Describes approaches to elicit the utility function Reviews classical and Bayesian approaches to statistical inference based on decision theory Discusses the role of causal analysis in statistical decision theory

Author : Shanti S. Gupta,James O. Berger
Publisher : Academic Press
Page : 550 pages
File Size : 52,7 Mb
Release : 2014-05-10
Category : Mathematics
ISBN : 9781483259550

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Statistical Decision Theory and Related Topics III by Shanti S. Gupta,James O. Berger Pdf

Statistical Decision Theory and Related Topics III, Volume 2 is a collection of papers presented at the Third Purdue Symposium on Statistical Decision Theory and Related Topics, held at Purdue University in June 1981. The symposium brought together many prominent leaders and a number of younger researchers in statistical decision theory and related areas. This volume contains the research papers presented at the symposium and includes works on general decision theory, multiple decision theory, optimum experimental design, sequential and adaptive inference, Bayesian analysis, robustness, and large sample theory. These research areas have seen rapid developments since the preceding Purdue Symposium in 1976, developments reflected by the variety and depth of the works in this volume. Statisticians and mathematicians will find the book very insightful.

Author : Samuel R. Houston,William L. Duff,Robert M. Lynch
Publisher : Unknown
Page : 84 pages
File Size : 48,9 Mb
Release : 1975
Category : Mathematics
ISBN : UOM:35128000148229

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Applications in Bayesian Decision Processes by Samuel R. Houston,William L. Duff,Robert M. Lynch Pdf

Author : William E. Pollard
Publisher : SAGE Publications, Incorporated
Page : 266 pages
File Size : 51,9 Mb
Release : 1986-02
Category : Mathematics
ISBN : UOM:39015012423383

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Bayesian Statistics for Evaluation Research by William E. Pollard Pdf

Introduction to Bayesian statistical methodology used as a measurement and evaluation technique in social sciences. Covers concepts of probability and inference decision making in statistical analysis.

Author : Shanti Swarup Gupta,James O. Berger
Publisher : Springer
Page : 537 pages
File Size : 51,6 Mb
Release : 1994
Category : Statistical decision
ISBN : 0387941436

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Statistical Decision Theory and Related Topics V by Shanti Swarup Gupta,James O. Berger Pdf

This volume comprises the invited papers at the Fifth Purdue Symposium on Statistical Decision Theory and Related Topics. The series of conferences is now well-established as presenting a superb state-of-the-art review of the subject. These papers are grouped into six parts which each give a detailed account of the latest theoretical and research developments in the areas of: A Retrospective on Wald's Decision Theory and Sequential Analysis, Asymptotics and Nonparametrics, Bayesian Analysis, Decision Theory and Selection Procedures, Probability and Probabilistic Structures, Sequential, Adaptive and Filtering problems. Consequently, this volume is ideally suited for researchers and graduate students in statistics and the decision sciences.

Author : John Geweke
Publisher : John Wiley & Sons
Page : 322 pages
File Size : 52,8 Mb
Release : 2005-10-03
Category : Mathematics
ISBN : 9780471744726

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Contemporary Bayesian Econometrics and Statistics by John Geweke Pdf

Tools to improve decision making in an imperfect world This publication provides readers with a thorough understanding of Bayesian analysis that is grounded in the theory of inference and optimal decision making. Contemporary Bayesian Econometrics and Statistics provides readers with state-of-the-art simulation methods and models that are used to solve complex real-world problems. Armed with a strong foundation in both theory and practical problem-solving tools, readers discover how to optimize decision making when faced with problems that involve limited or imperfect data. The book begins by examining the theoretical and mathematical foundations of Bayesian statistics to help readers understand how and why it is used in problem solving. The author then describes how modern simulation methods make Bayesian approaches practical using widely available mathematical applications software. In addition, the author details how models can be applied to specific problems, including: * Linear models and policy choices * Modeling with latent variables and missing data * Time series models and prediction * Comparison and evaluation of models The publication has been developed and fine- tuned through a decade of classroom experience, and readers will find the author's approach very engaging and accessible. There are nearly 200 examples and exercises to help readers see how effective use of Bayesian statistics enables them to make optimal decisions. MATLAB? and R computer programs are integrated throughout the book. An accompanying Web site provides readers with computer code for many examples and datasets. This publication is tailored for research professionals who use econometrics and similar statistical methods in their work. With its emphasis on practical problem solving and extensive use of examples and exercises, this is also an excellent textbook for graduate-level students in a broad range of fields, including economics, statistics, the social sciences, business, and public policy.