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Frontiers of Statistical Decision Making and Bayesian Analysis

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Release : 2010-07-24
Genre : Mathematics
Kind : eBook
Book Rating : 446/5 ( reviews)

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Book Synopsis Frontiers of Statistical Decision Making and Bayesian Analysis by : Ming-Hui Chen

Download or read book Frontiers of Statistical Decision Making and Bayesian Analysis written by Ming-Hui Chen. This book was released on 2010-07-24. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Frontiers of Statistical Decision Making and Bayesian Analysis

Download Frontiers of Statistical Decision Making and Bayesian Analysis PDF Online Free

Author :
Release : 2010-08-05
Genre : Mathematics
Kind : eBook
Book Rating : 453/5 ( reviews)

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Book Synopsis Frontiers of Statistical Decision Making and Bayesian Analysis by : Ming-Hui Chen

Download or read book Frontiers of Statistical Decision Making and Bayesian Analysis written by Ming-Hui Chen. This book was released on 2010-08-05. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Statistical Decision Theory and Bayesian Analysis

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Release : 2013-03-14
Genre : Mathematics
Kind : eBook
Book Rating : 86X/5 ( reviews)

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Book Synopsis Statistical Decision Theory and Bayesian Analysis by : James O. Berger

Download or read book Statistical Decision Theory and Bayesian Analysis written by James O. Berger. This book was released on 2013-03-14. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Optimal Statistical Decision & Bayesian Inference in Statistical Analysis & Applied Statistical Decision Theory

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Release : 2006-05-19
Genre : Mathematics
Kind : eBook
Book Rating : 887/5 ( reviews)

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Book Synopsis Optimal Statistical Decision & Bayesian Inference in Statistical Analysis & Applied Statistical Decision Theory by : Morris H. DeGroot

Download or read book Optimal Statistical Decision & Bayesian Inference in Statistical Analysis & Applied Statistical Decision Theory written by Morris H. DeGroot. This book was released on 2006-05-19. Available in PDF, EPUB and Kindle. Book excerpt: 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.

An Introduction to Bayesian Statistical Decision Processes

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Author :
Release : 1968
Genre : Bayesian statistical decision theory
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis An Introduction to Bayesian Statistical Decision Processes by : Bruce W. Morgan

Download or read book An Introduction to Bayesian Statistical Decision Processes written by Bruce W. Morgan. This book was released on 1968. Available in PDF, EPUB and Kindle. Book excerpt:

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