Bayesian Hierarchical Models - Couverture souple

Congdon, Peter D.

 
9781032177151: Bayesian Hierarchical Models
Couverture souple
ISBN 10 : 1032177152 ISBN 13 : 9781032177151
Editeur : Chapman and Hall/CRC, 2021

Synopsis

An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods.

The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples.

The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities.

Features:

  • Provides a comprehensive and accessible overview of applied Bayesian hierarchical modelling

  • Includes many real data examples to illustrate different modelling topics

  • R code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementation

  • Software options and coding principles are introduced in new chapter on computing

  • Programs and data sets available on the book's website

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l?auteur

Peter Congdon is Research Professor in Quantitative Geography and Health Statistics at Queen Mary, University of London.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Chapman and Hall/CRC
Date d'édition
2021
Langue
anglais
ISBN 10 
1032177152
ISBN 13 
9781032177151
Reliure
Broché
Numéro d'édition
2
Nombre de pages
592
Coordonnées du fabricant
non disponible
Personne responsable
non disponible

Autres éditions populaires du même titre

9781498785754: Bayesian Hierarchical Models: With Applications Using R

Edition présentée

ISBN 10 :  1498785751 ISBN 13 :  9781498785754
Editeur : Chapman & Hall/CRC, 2019
Couverture rigide