Bayesian Hierarchical Models

Congdon, Peter D.

ISBN 10: 1498785751 ISBN 13: 9781498785754
Published by Chapman and Hall/CRC, 2019
New Hardcover

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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

About the Author:

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

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Bibliographic Details

Title: Bayesian Hierarchical Models
Publisher: Chapman and Hall/CRC
Publication Date: 2019
Binding: Hardcover
Condition: Brand New
Edition: 2nd Edition

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