There has been a dramatic growth in the development and application of Bayesian inferential methods. This book introduces Bayesian modeling by the use of computation using the R language. The new edition contains changes in the R code illustrations.

Introduces Bayesian modeling by use of computation using the R language Includes supplementary material: sn.pub/extras

Autorentext

Maria Rizzo is professor of statistics at Bowling Green State University. Her recent book publications include Statistical Computing with R, 2e (2019) and Energy Statistics (forthcoming). Jim Albert is professor of mathematics and statistics at Bowling Green State University. His recent book publications include Analyzing Baseball Data with R, 2e (with Max Marchi and Benjamin S. Baumer, 2018), Visualizing Baseball (2017), and Bayesian Computation with R (Springer 2009).

Inhalt
An Introduction to R.- to Bayesian Thinking.- Single-Parameter Models.- Multiparameter Models.- to Bayesian Computation.- Markov Chain Monte Carlo Methods.- Hierarchical Modeling.- Model Comparison.- Regression Models.- Gibbs Sampling.- Using R to Interface with WinBUGS.