Bayesian Core

A Practical Approach to Computational Bayesian Statistics

Jean-Michel Marin, Christian Robert - Collection Springer texts in statistics

260 pages, parution le 01/02/2007

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Résumé

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.

L'auteur - Christian Robert

Actuaire et Docteur en Mathématiques Appliquées, Christian Robert enseigne l'économétrie de l'assurance à l'Ecole Nationale de la Statistique et de l'Administration Economique et au Conservatoire National des Arts et Métiers.

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Sommaire

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

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Jean-Michel Marin, Christian Robert
Collection	Springer texts in statistics
Parution	01/02/2007
Nb. de pages	260
Couverture	Relié
Intérieur	Noir et Blanc
EAN13	9780387389790
ISBN13	978-0-387-38979-0