Bayesian statistical modelling /
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| Author / Creator: | Congdon, P. |
|---|---|
| Imprint: | Chichester, England ; New York : John Wiley, c2001. |
| Description: | x, 531 p. : ill. ; 24 cm. |
| Language: | English |
| Series: | Wiley series in probability and statistics |
| Subject: | |
| Format: | Print Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/4443641 |
Table of Contents:
- Preface
- Chapter 1. Introduction: The Bayesian Method, its Benefits and Implementation
- Chapter 2. Bayesian Model Choice, Comparison and Checking
- Chapter 3. The Major Densities and their Application
- Chapter 4. Normal Linear Regression, General Linear Models and Log-Linear Models
- Chapter 5. Hierarchical Priors for Pooling Strength and Overdispersed Regression Modelling
- Chapter 6. Discrete Mixture Priors
- Chapter 7. Multinomial and Ordinal Regression Models
- Chapter 8. Time Series Models
- Chapter 9. Modelling Spatial Dependencies
- Chapter 10. Nonlinear and Nonparametric Regression
- Chapter 11. Multilevel and Panel Data Models
- Chapter 12. Latent Variable and Structural Equation Models for Multivariate Data
- Chapter 13. Survival and Event History Analysis
- Chapter 14. Missing Data Models
- Chapter 15. Measurement Error, Seemingly Unrelated Regressions, and Simultaneous Equations
- Appendix 1. A Brief Guide to Using Winbugs
- Index
