Bayesian Essentials with R

User's Manual.- Normal Models.- Regression and Variable Selection.- Generalized Linear Models.- Capture-Recapture Experiments.- Mixture Models.- Time Series.- Image Analysis.- References.- Index.

Jean-Michel Marin is Professor of Statistics at Université Montpellier 2, France, and Head of the Mathematics and Modelling research unit. He has written over 40 papers on Bayesian methodology and computing, as well as worked closely with population geneticists over the past ten years.

Christian Robert is Professor of Statistics at Université Paris-Dauphine, France. He has written over 150 papers on Bayesian Statistics and computational methods and is the author or co-author of seven books on those topics, including The Bayesian Choice (Springer, 2001), winner of the ISBA DeGroot Prize in 2004. He is a Fellow of the Institute of Mathematical Statistics, the Royal Statistical Society and the American Statistical Society. He has been co-editor of the Journal of the Royal Statistical Society, Series B, and in the editorial boards of the Journal of the American Statistical Society, the Annals of Statistics, Statistical Science, and Bayesian Analysis. He is also a recipient of an Erskine Fellowship from the University of Canterbury (NZ) in 2006 and a senior member of the Institut Universitaire de France (2010-2015).

"The material covered is perhaps quite ambitious and covers more than an introductory course in Bayesian statistics. PhD students and all those who want to check the computational details of the Bayesian approach will find the book very useful and interesting. A lot of researchers using Bayesian approaches only through Winbugs will perhaps find this book as an excellent companion of how the methods work really and gain insight from this." (Dimitris Karlis, zbMATH 1380.62005, 2018)


"This book is a very helpful and useful introduction to Bayesian methods of data analysis. I found the use of R, the code in the book, and the companion R package, bayess, to be helpful to those who want to begin using Bayesian methods in dataanalysis. ... Overall this is a solid book and well worth considering by its intended audience." (David E. Booth, Technometrics, Vol. 58 (3), August, 2016)

"Jean-Michel Marin's and Christian P. Robert's book Bayesian Essentials with R provides a wonderful entry to statistical modeling and Bayesian analysis. ... Overall, this is a well-written and concise book that combines theoretical ideas with a wide range of practical applications in an excellent way. Consequently, it can be highly useful to researchers who need to use Bayesian tools to analyze their datasets and professors who have to teach or students enrolled in an introductory course on Bayesian statistics." (Ana Corberán Vallet, Biometrical Journal, Vol. 58 (2), 2016)