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An Introduction to Bayesian Analysis: Theory and Methods (Springer Texts in Statistics)


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Click here to buy An Introduction to Bayesian Analysis: Theory and Methods (Springer Texts in Statistics) by  Jayanta K. Ghosh, Mohan Delampady, and Tapas Samanta. An Introduction to Bayesian Analysis: Theory and Methods (Springer Texts in Statistics)
by Jayanta K. Ghosh, Mohan Delampady, and Tapas Samanta
Sales Rank: 279876
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List Price: $89.95
$61.08
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on 10-13-2008
Buy An Introduction to Bayesian Analysis: Theory and Methods (Springer Texts in Statistics) Now!

  • Hardcover: 352 pages
  • Publisher: Springer; 1 edition July 27, 2006
  • Language: English
  • ISBN-10: 0387400842
  • ISBN-13: 978-0387400846
  • Product Dimensions: 9.4 x 6.4 x 0.9 inches
  • Shipping Weight: 1.4 pounds

    Product Review


    From the reviews:

    "This text provides a unique blend of theory, methods and applications that is suitable for a one-semester course in Bayesian analysis." C.M. O'Brien for Short Book Reviews of the ISI, December 2006

    "The material of the book covers more than a one semester course and provides enough results for a second course. … the book is simultaneously useful for different readership groups. Instructors will get guidelines for preparing a course on Bayesian statistics … . Students will enjoy the excellently clear … style and the exercises at the end of each chapter. Practitioners will find plenty of classical and recent Bayesian methods. … I highly recommend the book to all readers who are interested in Bayesian statistics." (Friedrich Liese, Mathematical Reviews, Issue, 2007 g)

    "This book, with its 10 chapters, represents a valuable introduction to Bayesian statistics and varies among theory, methods and applications. … The book’s material is invaluable, and is presented with clarity … . Each chapter’s topics are covered by various examples and many exercises. … gives a constructive approach to the statistical analysis based on Bayes’ formula. … So, it is strongly recommended to libraries and all who are interested in statistics." (Hassan S. Bakouch, Journal of Applied Statistics, Vol. 35 (3), 2008)

    "Taken overall, the book should be recommended to a wide audienceas a source of interesting and mind-provoking information about Bayesian statistics. " ( ISCB News, 2008)

    "Bayesian analysis have arrived. … This text offers one approach based on the pedagogic decision to ‘balance theory, methods, and applications.’ … The brief introduction to classical inference … provides a nice basis for the objective Bayesian treatment offered by the authors throughout the book. … this book appealing for classically trained statisticians. … Overall, I congratulate the authors for a largely successful attempt to introduce true religion." (C. Shane Reese, Journal of the American Statistical Association, Vol. 103 (482), June, 2008)

    Product Description


    This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate calculus and linear algebra, ideas of both subjective and objective Bayesian analysis are developed to a level where real-life data can be analyzed using the current techniques of statistical computing.

    Advances in both low-dimensional and high-dimensional problems are covered, as well as important topics such as empirical Bayes and hierarchical Bayes methods and Markov chain Monte Carlo (MCMC) techniques.

    Many topics are at the cutting edge of statistical research. Solutions to common inference problems appear throughout the text along with discussion of what prior to choose. There is a discussion of elicitation of a subjective prior as well as the motivation, applicability, and limitations of objective priors. By way of important applications the book presents microarrays, nonparametric regression via wavelets as well as DMA mixtures of normals, and spatial analysis with illustrations using simulated and real data. Theoretical topics at the cutting edge include high-dimensional model selection and Intrinsic Bayes Factors, which the authors have successfully applied to geological mapping.

    The style is informal but clear. Asymptotics is used to supplement simulation or understand some aspects of the posterior.

  • An Introduction to Bayesian Analysis: Theory and Methods (Springer Texts in Statistics)
    Available from Amazon
    Price: $61.08
    Updated on 10-13-2008

    Buy An Introduction to Bayesian Analysis: Theory and Methods (Springer Texts in Statistics) Now!


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