L'édition de cet ISBN n'est malheureusement plus disponible.
Afficher les exemplaires de cette édition ISBNJean-Michel Marin is Professor of Statistics at Université Montpellier 2, France, and Head of the Mathematics and Modelling research unit. He has written over 40 papers on Bayesian methodology and computing, as well as worked closely with population geneticists over the past ten years.
Christian Robert is Professor of Statistics at Université Paris-Dauphine, France. He has written over 150 papers on Bayesian Statistics and computational methods and is the author or co-author of seven books on those topics, including The Bayesian Choice (Springer, 2001), winner of the ISBA DeGroot Prize in 2004. He is a Fellow of the Institute of Mathematical Statistics, the Royal Statistical Society and the American Statistical Society. He has been co-editor of the Journal of the Royal Statistical Society, Series B, and in the editorial boards of the Journal of the American Statistical Society, the Annals of Statistics, Statistical Science, and Bayesian Analysis. He is also a recipient of an Erskine Fellowship from the University of Canterbury (NZ) in 2006 and a senior member of the Institut Universitaire de France (2010-2015).
This text focuses on the process of Bayesian analysis by integrating Bayesian theory, methods and computing to solve real data applications. Remarkably it accomplishes this in a straightforward, easy-to-understand manner. It starts with an introduction to Bayesian methods in simple normal models and ends with sophisticated applications in image analysis. Each chapter includes real data applications and extensive R code implementing the methods, all of which is included in the associated R package bayess. The text is ideally suited for use as an introduction to Bayesian methods and computing in undergraduate classes. --Galin Jones, School of Statistics, University of Minnesota
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Frais de port :
EUR 11,64
De Royaume-Uni vers Etats-Unis
Description du livre Etat : New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book. N° de réf. du vendeur ria9781493950492_lsuk
Description du livre PF. Etat : New. N° de réf. du vendeur 6666-IUK-9781493950492
Description du livre Etat : New. N° de réf. du vendeur 27201340-n
Description du livre Etat : New. N° de réf. du vendeur 27201340-n
Description du livre Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications.Readers are empowered to participate in the real-life data analysis situations depicted here from the beginning. 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. In particular, all R codes are discussed with enough detail to make them readily understandable and expandable.Bayesian Essentials with R can be used as a textbook at both undergraduate and graduate levels. It is particularly useful with students in professional degree programs and scientists to analyze data the Bayesian way. The text will also enhance introductory courses on Bayesian statistics. Prerequisites for the book are an undergraduate background in probability and statistics, if not in Bayesian statistics. 312 pp. Englisch. N° de réf. du vendeur 9781493950492
Description du livre Etat : New. Buy with confidence! Book is in new, never-used condition. N° de réf. du vendeur bk1493950495xvz189zvxnew
Description du livre Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. N° de réf. du vendeur C9781493950492
Description du livre Etat : New. N° de réf. du vendeur I-9781493950492
Description du livre Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. New Complete Solutions Manual for readers available on Springer book pageNo prior knowledge of R required to learn the essentials for using it with Bayesian statisticsEach chapter includes exercises that are both methodology and data-based. N° de réf. du vendeur 220487060
Description du livre Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications.Readers are empowered to participate in the real-life data analysis situations depicted here from the beginning. 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. In particular, all R codes are discussed with enough detail to make them readily understandable and expandable.Bayesian Essentials with R can be used as a textbook at both undergraduate and graduate levels. It is particularly useful with students in professional degree programs and scientists to analyze data the Bayesian way. The text will also enhance introductory courses on Bayesian statistics. Prerequisites for the book are an undergraduate background in probability and statistics, if not in Bayesian statistics. N° de réf. du vendeur 9781493950492