Description: Bayesian Hierarchical Models Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). With Applications Using R, Second Edition Author(s): Peter D. Congdon Format: Hardback Publisher: Taylor & Francis Inc, United States Imprint: Productivity Press ISBN-13: 9781498785754, 978-1498785754 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
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Location: Aldershot
End Time: 2025-01-12T09:29:36.000Z
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Book Title: Bayesian Hierarchical Models
Item Height: 254 mm
Item Width: 178 mm
Author: Peter D. Congdon
Publication Name: Bayesian Hierarchical Models: with Applications Using R, Second Edition
Format: Hardcover
Language: English
Publisher: Taylor & Francis INC International Concepts
Subject: Biology, Mathematics
Publication Year: 2019
Type: Textbook
Item Weight: 1211 g
Number of Pages: 580 Pages
