An introduction to applied Bayesian analysis using the market's standard tool, WinBUGS software, to conduct the types of modeling ecologists practice every day
1. Introduction
2. Principles of Bayesian Statistics
3. WinBUGS
4. A First Session in WinBUGS
5. Running WinBUGS from R via R2WinBUGS
6. Key Components of Generalized Linear Models
7. T-Test, Normal Linear Regression
8. Normal One-Way ANOVA
9. Interaction, General Linear Model
10. Linear Mixed-Effects Model
11. Introduction to the Generalized Linear Model (GLM)
12. Overdispersion and Offsets in the GLM
13. Poisson ANCOVA
14. Poisson Mixed-Effects Model
15. Binomial T-Test
16. Binomial ANCOVA
17. Binomial Mixed-Effects Model
18. Non-Standard GLMMs 1
19. Non-Standard GLMMs 2
20. Conclusion and Outlook
Acknowledgements
References
Dr. Marc works as a senior scientist at the Swiss Ornithological Institute, Seerose 1, 6204 Sempach, Switzerland. This is a non-profit NGO with about 160 employees dedicated primarily to bird research, monitoring, and conservation. Marc was trained as a plant population ecologist at the Swiss Universities of Basel and Zuerich. After a 2-year postdoc at the (then) USGS Patuxent Wildlife Center in Laurel, MD. During the last 20 years he has worked at the interface between population ecology, biodiversity monitoring, wildlife management, and statistics. He has published more than 100 peer-reviewed journal articles and five textbooks on applied statistical modeling. He has also been very active in teaching fellow biologists and wildlife managers the concepts and tools of modern statistical analysis in their fields in workshops all over the world, something which goes together with his books, which target the same audiences.
"I don't believe this book was written with the goal of being treated as the primary text of an intro Bayesian statistics course. That said, it could prove to be a useful supplemental text for an introductory Bayesian course or even a linear models course. Although the book was geared towards ecologists, I believe it would be an excellent library addition for any applied modeler interested in applying Bayesian methodologies in their work."--The American Statistician
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