Principles of Uncertainty

<p>Praise for the first edition: </p><p><i><strong> <br><p>Principles of Uncertainty</p></strong> 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!</i><b>—Christian Robert <em>CHANCE</em></b></p><p>It's a lovely book one that I hope will be widely adopted as a course textbook.<br>—<b>Michael Jordan University of California Berkeley USA</b></p><p>Like the prize-winning first edition <b><i>Principles of Uncertainty</i></b> <b><i>Second Edition</i></b> 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.</p><p>Key Features: </p><ul> <p> </p> <li>First edition won the 2011 DeGroot Prize</li> <p> </p> <li>Well-written introduction to theory of Bayesian statistics</li> <p> </p> <li>Each of the introductory chapters begins by introducing one new concept or assumption</li> <p> </p> <li>Uses just-in-time mathematics—the introduction to mathematical ideas just before they are applied</li> </ul>