
Principles of Uncertainty
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Principles of Uncertainty
is a profound and mesmerising book on the foundations and principles of subjectivist or behaviouristic Bayesian analysis. ... the book is a pleasure to read. And highly recommended for teaching as it can be used at many different levels. ... A must-read for sure!-Christian Robert, CHANCEIt's a lovely book, one that I hope will be widely adopted as a course textbook.
-Michael Jordan, University of California, Berkeley, USA
Like the prize-winning first edition, Principles of Uncertainty, Second Edition is an accessible, comprehensive text on the theory of Bayesian Statistics written in an appealing, inviting style, and packed with interesting examples. It presents an introduction to the subjective Bayesian approach which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods. This new edition has been updated throughout and features new material on Nonparametric Bayesian Methods, the Dirichlet distribution, a simple proof of the central limit theorem, and new problems.
Key Features:
First edition won the 2011 DeGroot Prize
Well-written introduction to theory of Bayesian statistics
Each of the introductory chapters begins by introducing one new concept or assumption
Uses "just-in-time mathematics"-the introduction to mathematical ideas just before they are applied
Reviews / Votes
"...Overall, my enthusiasm for the book, its original (and of course subjective) defence of the Bayesian approach, and its highly enjoyable style, remains intact! Especially when backed by the proof-in-the pudidng 2017 Pragmatics of Uncertainty..."- Christian P. Robert, CHANCE 2020 'my enthusiasm for the book, its original (and of course, subjective) defense of the Bayesian approach, and its highly enjoyable style, remains intact, especially when backed by the proof-in-the pudding 2017 Pragmatics of Uncertainty, which I reviewed in a 2019 issue of CHANCE (32(1)).'
- Christian Robert (2021) Principles of Uncertainty (Second Edition), CHANCE, 34:1, 54-55, DOI: 10.1080/09332480.2021.1885939
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