The Bayesian Choice
through its decision-theoretic foundations, while the message contained in the other book and transmitted only through processing datasets is that the Bayesian methodology is a universal and multifaceted tool for data analysis. While introducing wider and less mathematical audiences to the elegance and simplicity of the Bayesian methodology in a shorter and therefore more focussed volume was also necessary, if only because some learnbetter from examplesthan fromtheory, I came to the conclusionthat there was no paradox in insisting on those foundations in another book! I am therefore immensely thankful to Jean-Michel Marin for initiating this epiphany (if I may rightly borrow this expression from Joyce!), as well as forseveralyearsofintensecollaboration. Similarly,theDeGrootPrizec- mittee of the ISBA—International Society for Bayesian Analysis—World meeting of 2004 in Valparaiso, Chile, greatly honored me by attributing to The Bayesian Choice this prestigious prize. In doing so, this committee highlighted the relevance of both foundations and implementation for the presentandfuture ofBayesianStatistics,when itstated thatthe“book sets a new standard for modern textbooks dealing with Bayesian methods, es- cially those using MCMC techniques, and that it is a worthy successor to DeGroot’s and Berger’s earlier texts”. I am quite indebted to the members of the committee for this wonderful recognition. Third, it has been more than 18 years since I started working with John Kimmel from Springer New York (on a basic Probability textbook with Arup Bose that never materialized), and I always appreciated the support heprovidedoverthevariouseditionsofthebooks.
New in paperback, winner of the 2004 DeGroot Prize