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Bayesian Data Analysis

Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin
Publisher: 
Chapman & Hall/CRC
Publication Date: 
2013
Number of Pages: 
661
Format: 
Hardcover
Edition: 
3
Series: 
Texts in Statistical Science
Price: 
69.95
ISBN: 
9781439840955
Category: 
Textbook
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FUNDAMENTALS OF BAYESIAN INFERENCE
Probability and Inference
Single-Parameter Models
Introduction to Multiparameter Models
Asymptotics and Connections to Non-Bayesian Approaches
Hierarchical Models

FUNDAMENTALS OF BAYESIAN DATA ANALYSIS
Model Checking
Evaluating, Comparing, and Expanding Models
Modeling Accounting for Data Collection
Decision Analysis

ADVANCED COMPUTATION
Introduction to Bayesian Computation
Basics of Markov Chain Simulation
Computationally Efficient Markov Chain Simulation
Modal and Distributional Approximations

REGRESSION MODELS
Introduction to Regression Models
Hierarchical Linear Models
Generalized Linear Models
Models for Robust Inference 
Models for Missing Data

NONLINEAR AND NONPARAMETRIC MODELS 
Parametric Nonlinear Models
Basic Function Models
Gaussian Process Models
Finite Mixture Models
Dirichlet Process Models

APPENDICES
A: Standard Probability Distributions
B: Outline of Proofs of Asymptotic Theorems
C: Computation in R and Stan

Dummy View - NOT TO BE DELETED