Bayesian Core: A practical approach to computational Bayesian statistics

Marin, Jean-Michel; Robert, Christian P.

Marin, Jean-Michel; Robert, Christian P. (2007), Bayesian Core: A practical approach to computational Bayesian statistics, Springer Verlag : New York, p. 258. http://dx.doi.org/10.1007/978-0-387-38983-7

Type

Ouvrage

External document link

http://www.ceremade.dauphine.fr/~xian/BCS/

Date

2007

Publisher

Springer Verlag

Series title

Springer Texts in Statistics

Published in

New York

ISBN

978-0-387-38979-2

Pages

258

Abstract (FR)

Ce livre de modélisation bayésienne s'adresse aux praticiens en tant qu'ouvrage de formation à la statistique bayésienne. Il fournit une méthodologie opérationnelle pour la conduite de la statistique bayésienne, au travers d'études de cas résolues et de programmes R discutés. Ce livre peut être utilisé aux niveaux graduate et undergraduate, sous réserve d'une formation en probabilité et en statistique mathématique.

Abstract (EN)

This Bayesian modeling book is intended for practitioners and applied statisticians looking for a self-contained entry to computational Bayesian statistics. Focusing on standard statistical models and backed up by discussed real datasets available from the book website, it provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical justifications. Special attention is paid to the derivation of prior distributions in each case and specific reference solutions are given for each of the models. Similarly, computational details are worked out to lead the reader towards an effective programming of the methods given in the book.

Subjects / Keywords

Simulation; Statistique bayésienne

JEL

C44 - Operations Research; Statistical Decision Theory
C11 - Bayesian Analysis: General