Bayesian Essentials with R
This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an ope
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Jean-Michel Marin Christian Robert
Bayesian Essentials with R Second Edition
Springer Texts in Statistics Series Editors: George Casella Richard DeVeaux Stephen E. Fienberg Ingram Olkin
For further volumes: http://www.springer.com/series/417
Jean-Michel Marin • Christian P. Robert
Bayesian Essentials with R Second Edition
123
Jean-Michel Marin Universit´e Montpellier 2 Montpellier, France
Christian P. Robert Universit´e Paris-Dauphine Paris, France
ISSN 1431-875X ISSN 2197-4136 (electronic) ISBN 978-1-4614-8686-2 ISBN 978-1-4614-8687-9 (eBook) DOI 10.1007/978-1-4614-8687-9 Springer New York Heidelberg Dordrecht London Library of Congress Control Number: 2013950378 © Springer Science+Business Media New York 2014 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
To our most rewarding case studies, Chlo´e & Lucas, Joachim & Rachel
Preface
After that, it was down to attitude. —Ian Rankin, Black & Blue.— The purpose of this book is to provide a self-contained entry into practical and computational Bayesian statistics using generic examples from the most common models for a class duration of about seven blocks that roughly correspond to 13–15 weeks of teaching (with three hours of lectures per week), depending on the intended level and the prerequisites imp
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