Subjective and Objective Bayesian Statistics
Principles, Models, and Applications
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This second edition of Bayesian Statisticsexpands and updates the classic text in the field. It features new findings and even more applications to support the usefulness of the material. Neither too technical nor too simplistic, this accessible survey of an important field strikes the perfect balance between theory and application.
_ Shorter, more concise chapters provide flexible coverage of the subject.
_ Expanded coverage includes: uncertainty and randomness, prior distributions, predictivism, estimation, analysis of variance, and classification and imaging.
_ Includes topics not covered in other books, such as the de Finetti Transform.
_ Author S. James Press is the modern guru of Bayesian statistics.
_ Expanded coverage includes: uncertainty and randomness, prior distributions, predictivism, estimation, analysis of variance, and classification and imaging.
_ Includes topics not covered in other books, such as the de Finetti Transform.
_ Author S. James Press is the modern guru of Bayesian statistics.
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