Peter D. Congdon

Bayesian Hierarchical Models (eBook, PDF)

With Applications Using R, Second Edition

• Format: PDF

Produktbeschreibung

This is the second edition of a book on applied Bayesian modelling using WinBUGS. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 592
• Erscheinungstermin: 16. September 2019
• Englisch
• ISBN-13: 9781498785914
• Artikelnr.: 57730445

Autorenporträt

Peter Congdon is Research Professor in Quantitative Geography and Health Statistics at Queen Mary, University of London.

Inhaltsangabe

Contents
Preface
1. Bayesian Methods for Complex Data: Estimation and Inference
2. Bayesian Analysis Options in R, and Coding for BUGS, JAGS, and Stan
3. Model Fit, Comparison, and Checking
4. Borrowing Strength via Hierarchical Estimation
5. Time Structured Priors
6. Representing Spatial Dependence
7. Regression Techniques Using Hierarchical Priors
8. Bayesian Multilevel Models
9. Factor Analysis, Structural Equation Models, and Multivariate Priors
10. Hierarchical Models for Longitudinal Data
11. Survival and Event History Models
12. Hierarchical Methods for Nonlinear and Quantile Regression