Bayesian statistical modelling /
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| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Chichester, England ; Hoboken, NJ :
John Wiley & Sons,
[2006]
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| Edition: | 2nd ed. |
| Series: | Wiley series in probability and statistics.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Introduction : the Bayesian method, its benefits and implementation
- Bayesian model choice, comparison and checking
- The major densities and their application
- Normal linear regression, general linear models and log-linear models
- Hierarchical priors for pooling strength and overdispersed regression modelling
- Discrete mixture priors
- Multinomial and ordinal regression models
- Time series models
- Modelling spatial dependencies
- Nonlinear and nonparametric regression
- Multilevel and panel data models
- Latent variable and structural equation models for multivariate data
- Survival and event history analysis
- Missing data models
- Measurement error, seemingly unrelated regressions, and simultaneous eqations.