Research Catalog
Bayesian data analysis / Andrew Gelman ... [et al.].
- Title
- Bayesian data analysis / Andrew Gelman ... [et al.].
- Publication
- Boca Raton, Fla. : Chapman & Hall/CRC, c2004.
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1 Item
| Status | Format | Access | Call Number | Item Location |
|---|---|---|---|---|
| Text | Request in advance | QA279.5 .B386 2004 | Off-site |
Details
- Additional Authors
- Gelman, Andrew
- Description
- xxv, 668 p. : ill., maps; 25 cm.
- Summary
- The second edition of Bayesian Data Analysis continues to emphasize practice over theory, clearly describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide detailed guidance on all aspects of Bayesian data analysis and include many examples of real statistical analyses, based on their own research.
- Series Statement
- Texts in statistical science
- Uniform Title
- Texts in statistical science.
- Subjects
- Bayes Theorem
- Data Interpretation, Statistical > analysis
- Bayes-Verfahren
- Teoria da decisão (inferência estatística)
- Methode van Bayes
- Inferência paramétrica
- Inferência bayesiana (inferência estatística)
- Data-analyse
- Besliskunde
- Análise de dados
- Bayes-Entscheidungstheorie
- Datenanalyse
- Statistique bayésienne
- Bayesian statistical decision theory
- Statistics
- Bibliography (note)
- Includes bibliographical references (p. 611-646) and indexes.
- Processing Action (note)
- committed to retain
- Contents
- Part I: Fundamentals of Bayesian inference -- Background -- Single-parameter models -- Introduction to multiparameter models -- Large-sample inference and frequency properties of Bayesian inference -- Part II: Fundamentals of Bayesian data analysis -- Hierarchical models -- Model checking and improvement -- Modeling accounting for data collection -- Connections and challenges -- General advice -- Part III: Advanced computation -- Overview of computation -- Posterior simulation -- Approximations based on posterior modes -- Special topics in computation -- Part IV: Regression models -- Introduction to regression models -- Hierarchical linear models -- Generalized linear models -- Models for robust inference -- Part V: Specific models and problems -- Mixture models -- Multivariate models -- Nonlinear models -- Models for missing data -- Decision analysis -- Appendixes. Standard probability distributions -- Outline of proofs of asymptotic theorems -- Example of computation in R and Bugs.
- ISBN
- 158488388X (alk. paper)
- 9781584883883 (alk. paper)
- 9780203491287 (electronic bk.)
- 0203491289 (electronic bk.)
- LCCN
- ^^2003051474
- OCLC
- 51991499
- SCSB-11015610
- Owning Institutions
- Harvard Library