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Bayesian statistical decision theory

  • Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectivesby Andrew Gelman; Xiao-Li Meng

    Wiley 2004; US$ 140.00

    "I congratulate the editors on this volume; it really is an essential and very enjoyable journey with Don Rubin's statistical family." ( Biometrics , September 2006) "…contains much current important work…" ( Technometrics , November 2005) "This a useful reference book on an important topic with applications to a wide range of disciplines."... more...

  • Applied Bayesian Modellingby Peter Congdon

    Wiley 2003; US$ 146.00

    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... more...

  • Applied Bayesian Modellingby Peter Congdon

    Wiley 2014; US$ 90.95

    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... more...

  • Approximation Methods for Efficient Learning of Bayesian Networksby C. Riggelsen

    IOS Press 2008; US$ 119.00

    This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. For large amounts of incomplete data when Monte Carlo methods are inefficient, approximations are implemented, such that learning remains feasible,... more...

  • Bayes Linear Statistics, Theory & Methodsby Michael Goldstein; David Wooff

    Wiley 2007; US$ 179.00

    Michael Goldstein, Professor of Statistics, Department of Mathematical Sciences, University of Durham Michael Goldstein has worked on and researched the Bayes linear approach for around 30 years, his general interests being in the foundations, methodology and applications of Bayesian/subjectivist approaches to statistics. He has an outstanding... more...

  • Bayesian Approaches to Clinical Trials and Health-Care Evaluationby David J. Spiegelhalter; Keith R. Abrams; Jonathan P. Myles

    Wiley 2004; US$ 94.00

    "This is a terrific book and should be on the shelf of every professional that works in clinical trials or health-care evaluation. It gives a thorough pragmatic introduction to Bayesian methods for health-care interventions, provides many example along with data and software to reproduce the analyses, guides readers to areas where Bayesian methods... more...

  • Bayesian Argumentationby Frank Zenker

    Springer 2012; US$ 129.00

    Relevant to, and drawing from, a range of disciplines, the chapters in this collection show the diversity, and applicability, of research in Bayesian argumentation. Together, they form a challenge to philosophers versed in both the use and criticism of Bayesian models who have largely overlooked their potential in argumentation. Selected from contributions... more...

  • Bayesian Artificial Intelligenceby Kevin B. Korb; Ann E. Nicholson

    Taylor and Francis 2003; US$ 104.95

    As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical... more...

  • Bayesian Artificial Intelligence, Second Editionby Kevin B. Korb; Ann E. Nicholson

    Taylor and Francis 2010; US$ 104.95

    Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors... more...

  • Bayesian Computation with Rby

    Springer New York 2009; US$ 59.95

    There has been a dramatic growth in the development and application of Bayesian inferential methods. Some of this growth is due to the availability of powerful simulation-based algorithms to summarize posterior distributions. There has been also a growing interest in the use of the system R for statistical analyses. R's open source nature, free... more...