Introduction to WinBUGS for Ecologists
Bayesian Approach to Regression, ANOVA, Mixed Models and Related Analyses

An introduction to applied Bayesian analysis using the market’s standard tool, WinBUGS software, to conduct the types of modeling ecologists practice every day

Marc Kéry (Author)

9780123786050, Elsevier Science

Paperback / softback, published 19 July 2010

320 pages, 79 illustrations (79 in full color)
22.9 x 15.1 x 2.1 cm, 0.75 kg

"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

Introduction to WinBUGS for Ecologists introduces applied Bayesian modeling to ecologists using the highly acclaimed, free WinBUGS software. It offers an understanding of statistical models as abstract representations of the various processes that give rise to a data set. Such an understanding is basic to the development of inference models tailored to specific sampling and ecological scenarios. The book begins by presenting the advantages of a Bayesian approach to statistics and introducing the WinBUGS software. It reviews the four most common statistical distributions: the normal, the uniform, the binomial, and the Poisson. It describes the two different kinds of analysis of variance (ANOVA): one-way and two- or multiway. It looks at the general linear model, or ANCOVA, in R and WinBUGS. It introduces generalized linear model (GLM), i.e., the extension of the normal linear model to allow error distributions other than the normal. The GLM is then extended contain additional sources of random variation to become a generalized linear mixed model (GLMM) for a Poisson example and for a binomial example. The final two chapters showcase two fairly novel and nonstandard versions of a GLMM. The first is the site-occupancy model for species distributions; the second is the binomial (or N-) mixture model for estimation and modeling of abundance.

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

Subject Areas: Ecological science, the Biosphere [PSAF], Probability & statistics [PBT]