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Bayesian choice

Librairie Eyrolles - Paris 5e

Bayesian choice

Bayesian choice

Christian P. Robert

604 pages, parution le 01/04/2001 (2eme édition)


This graduate-level textbook presents an introduction to Bayesian statistics and decision theory. Its scope covers both the basic ideas of statistical theory, and also some of the more modern and advanced topics of Bayesian statistics such as complete class theorems, the Stein effect, Bayesian model choice, hierarchical and empirical Bayes modeling, Monte Carlo integration, including Gibbs sampling and other MCMC techniques. The second edition includes a new chapter on model choice (Chapter 7) and the chapter on Bayesian calculations (6) has been extensively revised. Chapter 4 includes a new section on dynamic models. In Chapter 3, the material on noninformative priors has been expanded, and Chapter 10 has been supplemented with more examples. The Bayesian Choice will be suitable as a text for courses on Bayesian analysis, decision theory or a combination of them. Christian P. Robert is Professor of Statistics in the Applied Mathematics Department at the Université Paris Dauphine, and external lecturer at Ecole Polytechnique, Palaiseau, France. He was previously Head of the Statistics Laboratory at the Center for Research in Economics and Statistics (CREST) of the National Institute for Statistics and Economic Studies (INSEE) in Paris. In addition to many papers on Bayesian statistics, simulation methods, and decision theory, he has written three other books, including Monte Carlo Statistical Method (Springer 1999) with George Casella. He also edited Discretization and MCMC Convergence Assessment (Springer 1998). He has served or is serving as an associate editor for the Annals of Statistics, the Journal of the American Statistical Association, Statistical Science, and Sankhya. He is a fellow of the Institute of Mathematical Statistics, and the Young Statistician Award of the Société de Statistique de Paris in 1995.

Keywords: Bayesian choice, Bayesian statistics, decision theory, Monte Carlo methods

Contents: Decision-theoretic foundations of statistical inference.- From prior information to prior distributions.- Bayesian point estimation.- Tests and confidence regions.- Bayesian Calculations.- Model Choice.- Admissibility and complete classes.- Invariance, Haar measures, and equivariant estimators.- Hierarchical and empirical Bayes extensions.- A defense of the Bayesian choice.

L'auteur - Christian P. Robert

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Caractéristiques techniques

Éditeur(s) Springer
Auteur(s) Christian P. Robert
Parution 01/04/2001
Édition  2eme édition
Nb. de pages 604
Format 15,8 x 24
Couverture Relié
Poids 1018g
Intérieur Noir et Blanc
EAN13 9780387952314
ISBN13 978-0-387-95231-4

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