Frontiers of Statistical Decision Making and Bayesian Analysis

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.
Ming-Hui Chen is Professor of Statistics at the University of Connecticut; Dipak K. Dey is Head and Professor of Statistics at the University of Connecticut; Peter Müller is Professor of Biostatistics at the University of Texas M. D. Anderson Cancer Center; Dongchu Sun is Professor of Statistics at the University of Missouri- Columbia; and Keying Ye is Professor of Statistics at the University of Texas at San Antonio.

Download Now
Read Online

Here is Download Link

Frontiers Of Statistical Decision Making And Bayesian Analysis


Frontiers Of Statistical Decision Making And Bayesian Analysis Download Now

Read Online

Author by : Ming-Hui Chen
Languange Used : en
Release Date : 2010-07-24
Publisher by : Springer Science & Business Media






Bayesian Statistics In Action


Bayesian Statistics In Action Download Now

Read Online

Author by : Raffaele Argiento
Languange Used : en
Release Date : 2017-04-28
Publisher by : Springer






Bayesian Statistics 9


Bayesian Statistics 9 Download Now

Read Online

Author by : José M. Bernardo
Languange Used : en
Release Date : 2011-10-06
Publisher by : Oxford University Press






2011


2011 Download Now

Read Online

Author by :
Languange Used : en
Release Date : 2011-01-01
Publisher by : Walter de Gruyter






Artificial Intelligence Frontiers In Statistics


Artificial Intelligence Frontiers In Statistics Download Now

Read Online

Author by : David J. Hand
Languange Used : en
Release Date : 1992-12-01
Publisher by : CRC Press






Foundations Of Linear And Generalized Linear Models


Foundations Of Linear And Generalized Linear Models Download Now

Read Online

Author by : Alan Agresti
Languange Used : en
Release Date : 2015-01-15
Publisher by : John Wiley & Sons






Improving Bayesian Reasoning What Works And Why


Improving Bayesian Reasoning What Works And Why Download Now

Read Online

Author by : Gorka Navarrete
Languange Used : en
Release Date : 2016-02-02
Publisher by : Frontiers Media SA






Leave a Reply

Your email address will not be published. Required fields are marked *