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Bayesian Data Analysis, Third Edition, 3rd Edition by Donald B. Rubin, Aki Vehtari, David B. Dunson, Hal S. Stern, John B. Carlin, Andrew Gelman

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Part IV: Regression Models

With modern computational tools at our disposal, we now turn to linear regression and generalized linear models, which are the statistical methods most commonly used to understand the relations between variables. Chapter 14 reviews classical regression from a Bayesian context, then Chapters 15 and 16 consider hierarchical linear regression and generalized linear models, along with the analysis of variance. Chapter 17 discusses robust alternatives to the standard normal, binomial, and Poisson distributions, and Chapter ...

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