Frontiers of Statistical Decision Making and Bayesian Analysis
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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.
From the reviews:
"The book is a 'Festschrift' in honour of Jim Berger's 60th birthday that was celebrated at a conference in spring 2010 in Texas. ... All the papers are written by experts in their fields and represent the current state of the art in Bayesian modelling. ... for those who are interested in Bayesian modelling, there are some interesting aspects to be detected. ... the book is aimed for advanced researchers in Bayesian analyses." (Wolfgang Polasek, International Statistical Review, Vol. 79 (3), 2011)
"This collection contains invited papers by statisticians to honor and acknowledge the contributions of James O. Berger to Bayesian statistics. These papers present recent surveys and developments within the area of statistical decision theory and Bayesian statistics and related topics. ... Each chapter ... provides a detailed treatment of the topic under consideration. ... can be useful for graduate students and researchers from diverse fields of statistics and related disciplines. ... this edited volume contains a wealth of knowledge, wisdom and information on Bayesian statistics." (Technometrics, Vol. 53 (2), May, 2011)
Herausgeber Ming-Hui Chen
Herausgeber Peter Müller
Herausgeber Dongchu Sun
Herausgeber Keying Ye
Herausgeber Dipak K. Dey
Größe 235 x 155 x 155 mm
Produktgewicht 2400 g