Bayesian data analysis

Bayesian data analysis / Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin.

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Bibliographic Details
Main Author:	Gelman, Andrew (Author)
Format:	Book
Language:	English
Published:	Boca Raton : CRC Press, 2014.
Edition:	Third edition.
Series:	Texts in statistical science.
Subjects:	Bayesian statistical decision theory.

Table of Contents:

Part I: Fundamentals of Bayesian inference. Probability and inference
Single-parameter models
Introduction to multiparameter models
Asymptotics and connections to non-Bayesian approaches
Hierarchical models
Part II: Fundamentals of Bayesian data analysis. Model checking
Evaluating, comparing, and expanding models
Modeling accounting for data collection
Decision analysis
Part III: Advanced computation. Introduction to Bayesian computation
Basics of Markov chain simulation
Computationally efficient Markov chain simulation
Modal and distributional approximations
Part IV: Regression models. Introduction to regression models
Hierarchical linear models
Generalized linear models
Models for robust inference
Models for missing data
Part V: Nonlinear and nonparametric models. Parametric nonlinear models
Basis function models
Gaussian process models
Finite mixture models
Dirichlet process models
A. Standard probability distributions
B. Outline of proofs of limit theorems
Computation in R and Stan.