Introduction to WinBUGS for Ecologists

Bayesian Approach to Regression, ANOVA, Mixed Models and Related Analyses

Marc Kéry, Marc Kery

• Publisher: Academic Press
• Year: 2010
• Print ISBN: 9780123786050
• eBook ISBN: 9780123786067
• Topic: Biological Sciences
• Subtopic: Ecology
• Index: Biological Sciences

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.- Introduction to the essential theories of key models used by ecologists- Complete juxtaposition of classical analyses in R and Bayesian analysis of the same models in WinBUGS- Provides every detail of R and WinBUGS code required to conduct all analyses- Companion Web Appendix that contains all code contained in the book and additional material (including more code and solutions to exercises)

Table of contents

• Cover image
• Table of Contents
• Front Matter
• Copyright
• A Creed for Modeling
• Foreword
• Preface
• Chapter 1. Introduction
• Chapter 2. Introduction to the Bayesian Analysis of a Statistical Model
• Chapter 3. WinBUGS
• Chapter 4. A First Session in WinBUGS
• Chapter 5. Running WinBUGS from R via R2WinBUGS
• Chapter 6. Key Components of (Generalized) Linear Models
• Chapter 7. t-Test
• Chapter 8. Normal Linear Regression
• Chapter 9. Normal One-Way ANOVA
• Chapter 10. Normal Two-Way ANOVA
• Chapter 11. General Linear Model (ANCOVA)
• Chapter 12. Linear Mixed-Effects Model
• Chapter 13. Introduction to the Generalized Linear Model
• Chapter 14. Overdispersion, Zero-Inflation, and Offsets in the GLM
• Chapter 15. Poisson ANCOVA
• Chapter 16. Poisson Mixed-Effects Model (Poisson GLMM)
• Chapter 17. Binomial “t-Test”
• Chapter 18. Binomial Analysis of Covariance
• Chapter 19. Binomial Mixed-Effects Model (Binomial GLMM)
• Chapter 20. Nonstandard GLMMs 1
• Chapter 21. Nonstandard GLMMs 2
• Chapter 22. Conclusions
• APPENDIX. A List of WinBUGS Tricks
• References
• Index