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Bayesian statistical decision theory

Most popular at the top

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

    Springer International Publishing 2015; US$ 109.00

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

    Springer New York 2008; US$ 199.00

    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...

  • Bayesian Statistical Modellingby Peter Congdon

    Wiley 2007; US$ 118.00

    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...

  • Bayesian Theoryby José M. Bernardo; Adrian F. M. Smith

    Wiley 2009; US$ 494.00

    This highly acclaimed text, now available in paperback, provides a thorough account of key concepts and theoretical results, with particular emphasis on viewing statistical inference as a special case of decision theory. Information-theoretic concepts play a central role in the development of the theory, which provides, in particular, a detailed discussion... more...

  • Data Analysisby Devinderjit Sivia; John Skilling

    Oxford University Press, UK 2006; US$ 50.00

    One of the strengths of this book is the author's ability to motivate the use of Bayesian methods through simple yet effective examples. - Katie St. Clair MAA Reviews more...

  • Die Theorie, die nicht sterben wollteby Sharon Bertsch McGrayne; Carl Freytag

    Springer Berlin Heidelberg 2013; US$ 29.99

    Die Autorin macht die Bedeutung des Bayes-Theorems einem breiten Publikum verständlich: von seiner Entdeckung im 18. Jahrhundert, der Weiterentwicklung durch Laplace über die vielen Kontroversen, die es ausgelöst hat, bis zur allgegenwärtigen Anwendung heute. more...

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

    Elsevier Science 2005; US$ 325.00

    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...

  • Hierarchical Modelling for the Environmental Sciencesby James S. Clark; Alan E. Gelfand

    Oxford University Press, UK 2006; US$ 124.99

    '...if you are already quite well acquainted with Bayesian concepts and terminology then this book should provide an excellent guide to the application of these advanced statistical techniques within ecology.' Justin Travis, Bulletin of the British Ecological Society 2007 38:1 - more...

  • Introduction to Bayesian Statisticsby William M. Bolstad

    Wiley 2013; US$ 160.00

    Praise for the First Edition "I cannot think of a better book for teachers of introductory statistics who want a readable and pedagogically sound text to introduce Bayesian statistics." — Statistics in Medical Research "[This book] is written in a lucid conversational style, which is so rare in mathematical writings. It does an excellent... more...

  • Introduction to Bayesian Statisticsby Karl-Rudolf Koch

    Springer Berlin Heidelberg 2007; US$ 169.00

    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...