Description

Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori. Begins with a discussion of some important general aspects of the Bayesian approach such as the choice of prior distribution, particularly noninformative prior distribution, the problem of nuisance parameters and the role of sufficient statistics, followed by many standard problems concerned with the comparison of location and scale parameters. The main thrust is an investigation of questions with appropriate analysis of mathematical results which are illustrated with numerical examples, providing evidence of the value of the Bayesian approach.

Bayesian Inference in Statistical Analysis

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£160.95

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Paperback / softback by George E. P. Box , George C. Tiao

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Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation... Read more

    Publisher: John Wiley & Sons Inc
    Publication Date: 21/04/1992
    ISBN13: 9780471574286, 978-0471574286
    ISBN10: 0471574287

    Number of Pages: 608

    Non Fiction , Mathematics & Science , Education

    Description

    Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori. Begins with a discussion of some important general aspects of the Bayesian approach such as the choice of prior distribution, particularly noninformative prior distribution, the problem of nuisance parameters and the role of sufficient statistics, followed by many standard problems concerned with the comparison of location and scale parameters. The main thrust is an investigation of questions with appropriate analysis of mathematical results which are illustrated with numerical examples, providing evidence of the value of the Bayesian approach.

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