Subjective and Objective Bayesian Statistics: Principles, Models, and Applications
Description:
- 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.
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