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Bayesian statistical decision theory

Most popular at the top

  • Bayesian Networks and Influence Diagramsby Uffe B. Kjaerulff; Anders L. Madsen

    Springer 2007; US$ 109.00

    Probabilistic networks have become one of the promising technologies in the area of applied artificial intelligence. This title provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. more...

  • Pratique du calcul bayésienby Jean-Jacques Boreux; Eric Parent; Jacques Bernier

    Springer 2010; US$ 39.95

    La premiere partie de cet ouvrage privilegie les modeles statistiques parametriques calculables a la main. Des le premier chapitre, la representation du modele par un graphe acyclique oriente permet de distinguer clairement la phase ou la creativite du chercheur s'exprime de celle ou il calcule. A cette fin, le logiciel libre WinBUGS sera tres... more...

  • Strategic Economic Decision-Makingby Jeff Grover

    Springer 2012; US$ 39.95

    Strategic Economic Decision-Making: Using Bayesian Belief Networks to Solve Complex Problems is a quick primer on the topic that introduces readers to the basic complexities and nuances associated with learning Bayes’ theory and inverse probability for the first time. This brief is meant for non-statisticians who are unfamiliar with Bayes’... more...

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

    Wiley 2004; US$ 94.00

    READ ALL ABOUT IT! David Spiegelhalter has recently joined the ranks of Isaac Newton, Charles Darwin and Stephen Hawking by becoming a fellow of the Royal Society. Originating from the Medical Research Council’s biostatistics unit, David has played a leading role in the Bristol heart surgery and Harold Shipman inquiries.   Order... 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 Logical Data Analysis for the Physical Sciencesby Phil Gregory

    Cambridge University Press 2005; US$ 50.00

    Increasingly, researchers in many branches of science are coming into contact with Bayesian statistics or Bayesian probability theory. This book provides a clear exposition of the underlying concepts with large numbers of worked examples and problem sets. Background material is provided in appendices and supporting Mathematica notebooks are available. more...

  • Multivariate Bayesian Statisticsby Daniel B. Rowe

    Taylor and Francis 2002; US$ 154.95

    Of the two primary approaches to the classic source separation problem, only one does not impose potentially unreasonable model and likelihood constraints: the Bayesian statistical approach. Bayesian methods incorporate the available information regarding the model parameters and not only allow estimation of the sources and mixing coefficients, but... more...

  • Handbook of Statisticsby Dipak K. Dey; C.R. Rao

    Elsevier Science 2005; US$ 315.00

    This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view. It further describes parametric and nonparametric Bayesian methods for modelling and how to use modern computational methods to summarize inferences using simulation. The book covers wide range of... more...

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

    Wiley 2007; US$ 173.00

    Bayesian methods combine information available from data with any prior information available from expert knowledge. The Bayes linear approach follows this path, offering a quantitative structure for expressing beliefs, and systematic methods for adjusting these beliefs, given observational data. The methodology differs from the full Bayesian methodology... more...

  • Bayesian Statistical Modellingby Peter Congdon

    Wiley 2007; US$ 114.00

    Bayesian methods combine the evidence from the data at hand with previous quantitative knowledge to analyse practical problems in a wide range of areas. The calculations were previously complex, but it is now possible to routinely apply Bayesian methods due to advances in computing technology and the use of new sampling methods for estimating parameters.... more...