Author: Christian P. Robert
Publisher: Springer Verlag, New York
Keywords: implementation, springer, texts, statistics, computational, foundations, choice, decision, theoretic, bayesian
Number of Pages: 577
Published: 2007-06-01
List price: $54.95
ISBN-10: 0387715983
ISBN-13: 9780387715988

WINNER OF THE 2003 DEGROOT PRIZE! The DeGroot Prize is awarded every two years by the International Society for Bayesian Analysis in recognition of an important, timely, thorough and notably original contribution to the statistics literature.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

Author: Christian P. Robert
Publisher: Springer
Keywords: probabilitã©s, appliquã©es, french, statistique, pratique, bayã©sien, principes, choix
Number of Pages: 638
Published: 2006-01-01
List price: $139.00
ISBN-10: 2287251731
ISBN-13: 9782287251733

Author: Christian M. Robert
Publisher: Elsevier Science
Keywords: paleoenvironment, developments, marine, geology, geodynamics, interplay, sedimentology, ocean, volume, global
Number of Pages: 496
Published: 2008-11-21
List price: $180.00
ISBN-10: 0444518177
ISBN-13: 9780444518170

This book provides an update of synthetic information in marine sedimentology, associating generalities to case studies. New information is replaced in a context of plate tectonics and evolution of ocean systems at geological scale. Besides general information, the book insists on the relationships between plate tectonics and sedimentation, as well as on the formation and evolution of sediment series and their potential as archives of past environments. * complete update of synthetic information in marine sedimentology.* association of information on the o

Author: Christian Robert
Publisher: Springer
Keywords: implementation, springer, texts, statistics, computational, foundations, choice, decision, theoretic, bayesian
Number of Pages: 577
Published: 2001-05-25
List price: $119.00
ISBN-10: 0387952314
ISBN-13: 9780387952314

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 MCMC techniques, and Gibbs sampling. 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

Author: Christian P. Robert
Publisher: Springer
Keywords: notes, statistics, lecture, assessment, mcmc, convergence, discretization
Number of Pages: 192
Published: 1998-08-13
List price: $84.95
ISBN-10: 0387985913
ISBN-13: 9780387985916

This monograph proposes several approaches to convergence monitoring for MCMC algorithms which are centered on the theme of discrete Markov chains. After a short introduction to MCMC methods, including recent developments like perfect simulation and Langevin Metropolis-Hastings algorithms, and to the current convergence diagnostics, the contributors present the theoretical basis for a study of MCMC convergence using discrete Markov chains and their specificities. The contributors stress in particular that this study applies in a wide generality, starting with latent variable models li

Authors:Christian P. Robert, George Casella,
Publisher: Springer
Keywords: texts, statistics, springer, methods, carlo, statistical, monte
Number of Pages: 645
Published: 2005-07-26
List price: $109.00
ISBN-10: 0387212396
ISBN-13: 9780387212395

Monte Carlo statistical methods, particularly those based on Markov chains, have now matured to be part of the standard set of techniques used by statisticians. This book is intended to bring these techniques into the classroom, being a self-contained logical development of the subject. This is a textbook intended for a second year graduate course. We do not assume that the reader has any familiarity with Monte Carlo techniques (such as random variable generation), or with any Markov chain theory. Chapters 1-3 are introductory, first reviewing various statistical methodologies, then covering t

Authors:Christian Robert, George Casella,
Publisher: Springer Verlag
Keywords: methods, carlo, monte, introducing
Number of Pages: 284
Published: 2009-12-10
List price: $64.95
ISBN-10: 1441915753
ISBN-13: 9781441915757

Computational techniques based on simulation have now become an essential part of the statistician’s toolbox. It is thus crucial to provide statisticians with a practical understanding of those methods, and there is no better way to develop intuition and skills for simulation than to use simulation to solve statistical problems. Introducing Monte Carlo Methods with R covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison. Whi