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Bayesian statistical decision theory

Most popular at the top

  • Risk Assessment and Decision Analysis with Bayesian Networksby Norman Fenton; Martin Neil

    CRC Press 2012; US$ 89.95

    Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian Networks explains how to incorporate knowledge with data to develop... more...

  • Bayesian Methodsby Jeff Gill

    CRC Press 2014; US$ 77.95

    An Update of the Most Popular Graduate-Level Introductions to Bayesian Statistics for Social Scientists Now that Bayesian modeling has become standard, MCMC is well understood and trusted, and computing power continues to increase, Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition focuses more on implementation details... more...

  • Bayesian Networksby Marco Scutari; Jean-Baptiste Denis

    CRC Press 2014; US$ 93.95

    Understand the Foundations of Bayesian Networks?Core Properties and Definitions Explained Bayesian Networks: With Examples in R introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples in R illustrate each step of the modeling process. The examples start from the simplest notions and gradually increase in complexity.... more...

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

    CRC Press 2010; US$ 114.95

    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 Missing Data Problemsby Ming T. Tan; Guo-Liang Tian; Kai Wang Ng

    CRC Press 2009; US$ 109.95

    Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors. The methods are based on the inverse Bayes formulae discovered by one of the author in 1995. Applying the Bayesian approach to important real-world... more...

  • Bayesian Nonparametric Data Analysisby Peter Müller; Fernando Andrés Quintana; Alejandro Jara; Tim Hanson

    Springer International Publishing 2015; US$ 84.23

    This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book?s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric... more...

  • Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysisby Uffe B. Kjærulff; Anders L. Madsen

    Springer New York 2007; US$ 77.72

    This book provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. The theory and methods presented are illustrated through more than 140 examples. more...

  • Bayesian Reliabilityby Michael S. Hamada; Alyson Wilson; C. Shane Reese; Harry Martz

    Springer New York 2008; US$ 157.24

    This book is a reference collection of modern Bayesian methods in reliability for use by reliability practitioners. There are more than 70 illustrative examples, most of which utilize real-world data. It can also be used as a textbook and contains more than 160 exercises. more...

  • Introduction to Bayesian Statisticsby Karl-Rudolf Koch

    Springer Berlin Heidelberg 2007; US$ 146.01

    This book presents Bayes? theorem, the estimation of unknown parameters, the determination of confidence regions and the derivation of tests of hypotheses for the unknown parameters. It does so in a simple manner that is easy to comprehend. The book compares traditional and Bayesian methods with the rules of probability presented in a logical way... more...

  • Bayesian Computation with Rby Jim Albert

    Springer New York 2009; US$ 45.40

    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...