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Bayesian Hierarchical Models : With Applications Using R, Second Edition by Peter D. Congdon is a nonfiction available to read on EtoBox.

What is Bayesian Hierarchical Models : With Applications Using R, Second Edition about?

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 densiti

Who reads Bayesian Hierarchical Models : With Applications Using R, Second Edition?

Author

Peter D. Congdon

Publisher

Chapman and Hall/CRC

Published

2020

Language

EN

ISBN

9781498785754

Category

nonfiction

Subjects

Mathematics, Computer Science, Stem