Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan
Key differences between 2nd and 1st editions
 Period between current and previous editions: 4 years (2014 vs 2010).
 In the Second Edition J. Kruschke presents all new programs in JAGS and Stan.
 New Chapter 3 on R Programming Language, which is used for the development of computer programs for statistics and data analysis.
 Two former separate chapters  Chapter 7 "Inferring a Binomial Proportion via the Metropolis Algorithm" and Chapter 8 "Inferring Two Binomial Proportions via Gibbs Sampling"  have been consolidated into a single Chapter 7 "Markov Chain Monte Carlo". This chapter now presents new material on Markov Chain Monte Carlo (MCMC) convergence diagnostic methods.
 Completely new Chapter 8 on Just another Gibbs sampler (JAGS), a program for investigation of Bayesian hierarchical models, written by Martyn Plumme.
 Chapter 9 includes new material on shrinkage in hierarchical models.
 New Chapter 10 "Model Comparison and Hierarchical Modeling" consolidated into a single chapter all the material on model comparison, which was spread across various chapters in the First edition.
 Chapter 10 now contains all the material on model comparison, which was spread across multiple chapters before.
 Chapter 11: new material on sampling distributions used to test hypotheses.
 Chapter 12: new material about the region of practical equivalence (ROPE); SavageDickey approximations to the Bayes factor.
 Chapter 13: new section 13.3 "Sequential Testing and the Goal of Precision".
 New Chapter 14 on Stan, an imperative probabilistic programming language.
 Chapter 16: new section 16.3 on metric predicted variable on two groups.
 Chapter 18: new section 18.4 "Variable Selection".
 Chapter 19: new examples on analysis of covariance (ANCOVA).
 Chapter 21 includes examples of robust logistic regression.
 New Chapter 22 "Nominal Predicted Variable" covers:
 Softmax regression (a form of multinomial logistic regression)
 Conditional (fixedeffects) logistic regression
 Implementation in JAGS (Just Another Gibbs Sampler)
 Models generalizations and variations
 Chapter 23 has examples showing singlegroup and twogroup analyses.
 Chapter 25: new section 25.4 "Censored Data in JAGS".
2nd Edition of
Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan
eBook, 746 pages
eBook ISBN: 9780124059160
Published by: Academic Press, November 11, 2014
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ISBN10: 0124058884
ISBN13: 9780124058880
Published by: Academic Press, November 17, 2014
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1st Edition of
Doing Bayesian Data Analysis: A Tutorial Introduction with R
eBook, 672 pages
eBook ISBN: 9780123814869
Published by: Academic Press, November 25, 2010
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Hardcover, 672 pages
ISBN10: 0123814855
ISBN13: 9780123814852
Published by: Academic Press, November 10, 2010
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