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 Trans
Subjective and Objective Bayesian Statistics: Principles, Models, and Applications (Wiley Series in Probability and Statistics)
โ Scribed by S. James Press
- Publisher
- Wiley-Interscience
- Year
- 2002
- Tongue
- English
- Leaves
- 591
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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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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 Trans
* 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
This is the most complete reliability book that I have seen. It is appropriate as both a textbook and a reference. It is well-written and easy to understand. I highly recommend this book for anybody interested in learning reliability theory.
The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new p