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Institute of Mathematical Statistics Textbooks
Computational Bayesian Statistics An Introduction
M. Antónia Amaral Turkman Carlos Daniel Paulino
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Universidade de Lisboa
and Peter Müller
University of Texas, Austin This book explains the fundamental ideas of Bayesian analysis, with a focus on computational methods such as MCMC and available software such as R/R-INLA, OpenBUGS, JAGS, Stan, and BayesX. It is suitable as a textbook for a first graduate-level course and as a user’s guide for researchers and graduate students from beyond statistics.
‘An introduction to computational Bayesian statistics cooked to perfection, with the right mix of ingredients, from the spirited defense of the Bayesian approach, to the description of the tools of the Bayesian trade, to a definitely broad and very much up-to-date presentation of Monte Carlo and Laplace approximation methods, to a helpful description of the most common software. And spiced up with critical perspectives on some common practices and a healthy focus on model assessment and model selection. Highly recommended on the menu of Bayesian textbooks!’
Christian Robert, Université de Paris IX, Paris-Dauphine, and University of Warwick
‘This book aims to be a concise introduction to modern computational Bayesian statistics, and it certainly succeeds! The authors carefully introduce every main technique that is around and demonstrate its use with the appropriate software. Additionally, the book contains a readable introduction to Bayesian methods, and brings the reader up to speed within the field in no time!’
Håvard Rue, King Abdullah University of Science and Technology, Saudi Arabia
Institute of Mathematical Statistics Textbooks, 11
2019 228 x 152 mm 254pp 12 b/w illus. 978-1-108-70374-1 Paperback £29.99 / US$39.99 For all formats available, see www.cambridge.org/9781108703741 Statistical Modelling by Exponential Families
Rolf Sundberg
Stockholms Universitet This readable, digestible introduction to exponential families of distributions covers the essential theory and demonstrates its use in applications. Containing a vast set of examples and numerous exercises, it is written for graduate students and researchers with a background in basic statistical inference.
‘Rolf Sundberg’s book gives attractive properties of the exponential family and illustrates them for a wide variety of applications. Definitions are concise and most propositions look directly appealing. The writing reflects the author’s experience in deriving results that are essential for good modelling and convincing inference. Thus, this book is indispensable for all data scientists, be they graduate students or experienced researchers.’
Nanny Wermuth, Chalmers tekniska högskola, Sweden
Institute of Mathematical Statistics Textbooks, 12
2019 228 x 152 mm 296pp 22 b/w illus. 100 exercises 978-1-108-70111-2 Paperback £29.99 / US$39.99 For all formats available, see www.cambridge.org/9781108701112