Product Details
| ISBN-13 | 9781439840955 |
|---|---|
| ISBN-10 | 1439840954 |
| Edition | 3rd |
| Authors | Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin |
| Publisher | CRC Press (Chapman & Hall/CRC Texts in Statistical Science) |
| Publication date | 2013 |
| Format | Hardcover |
| Language | English |
| Pages | 676 |
| Category | Physical Sciences & Mathematics |
| List price | $54.99 / copy |
| Min. order | 5 copies |
| Condition | New |
Description
Bayesian Data Analysis, Third Edition by Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin is the leading text on Bayesian methods, winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis. Graduate statistics and applied statistics programs can source it in bulk directly through Global Academic Supply.
Key Features
- 3rd edition hardcover, CRC Press (Chapman & Hall), 2013, 676 pages
- Five parts covering fundamentals of Bayesian inference, fundamentals of Bayesian data analysis, advanced computation, regression models, and nonlinear/nonparametric models
- New chapters (20-23) on basis function, Gaussian process, finite mixture, and Dirichlet process models
- Weakly informative and boundary-avoiding priors, updated cross-validation and predictive information criteria
- Hamiltonian Monte Carlo, variational Bayes, and expectation propagation coverage
- Appendices on standard probability distributions, limit theorem proofs, and computation in R and Stan
Specifications
- Authors: Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin
- Publisher: CRC Press (Chapman & Hall/CRC Texts in Statistical Science)
- Edition: 3rd
- Format: Hardcover, 676 pages
- ISBN-13: 9781439840955
- ISBN-10: 1439840954
- Publication date: 2013
Buy in Bulk from Global Academic Supply
Bayesian Data Analysis, Third Edition is available to order through Global Academic Supply at $52.99 per copy for 5+, $50.99 for 10+, and $47.99 for 25+, against a $54.99 list price. Institutions can pay by purchase order with Net-30 terms, and tax-exempt certificates are accepted for qualifying organizations.
About This Edition
Written by Andrew Gelman and colleagues, Bayesian Data Analysis is the field's definitive text, serving as an introductory text, a graduate text, and a handbook of applied Bayesian methods. It is a natural bulk title for graduate statistics and applied statistics programs teaching on the same edition.
Key Topics
- 3rd edition hardcover, CRC Press (Chapman & Hall), 2013, 676 pages
- Five parts covering fundamentals of Bayesian inference, fundamentals of Bayesian data analysis, advanced computation, regression models, and nonlinear/nonparametric models
- New chapters (20-23) on basis function, Gaussian process, finite mixture, and Dirichlet process models
- Weakly informative and boundary-avoiding priors, updated cross-validation and predictive information criteria
- Hamiltonian Monte Carlo, variational Bayes, and expectation propagation coverage
- Appendices on standard probability distributions, limit theorem proofs, and computation in R and Stan
Who This Is For
- Graduate statistics, biostatistics, and applied statistics programs teaching Bayesian inference, modeling, and computation.
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
Appendices: A. Standard Probability Distributions; B. Outline of Proofs of Limit Theorems; C. Computation in R and Stan
Institutional & Bulk Ordering
- Minimum order: 5 copies, with tiered pricing at higher quantities
- Purchase orders and Net-30 terms accepted for qualifying institutions
- Tax-exempt certificates accepted at checkout
- Free worldwide shipping, no sales tax
Edition & Identifier Check
Always confirm this exact ISBN-13 and edition (9781439840955) against your syllabus or procurement request before ordering — editions of this title are not interchangeable.
Frequently Asked Questions
Q: Who is this book for?
A: Graduate statistics, biostatistics, and applied statistics programs teaching Bayesian inference, modeling, and computation.
Q: What edition and format is this?
A: The 3rd edition, hardcover, published by CRC Press (Chapman & Hall) in 2013, 676 pages.
Q: What is new in the 3rd edition?
A: Four new chapters on nonparametric modeling (basis function, Gaussian process, finite mixture, and Dirichlet process models), weakly informative and boundary-avoiding priors, an updated cross-validation/predictive information criteria chapter, improved MCMC convergence monitoring, and new presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation.
Q: What bulk pricing tiers apply to this title?
A: $52.99 per copy for 5+, $50.99 for 10+, $47.99 for 25+, and a custom quote at 100+, against a $54.99 list price.
Q: Is it in stock for a bulk order?
A: Yes, it's currently in stock and available for bulk order.