Introduction to Win: BUGS for Ecologists. A Bayesian Approach to Regression, Anova, Mixed Models, and Related Analyses

✍ Scribed by Marc Kéry (Auth.)

• Publisher: Academic Press
• Year: 2010
• Tongue: English
• Leaves: 301
• Edition: 1
• Category: Library

✦ Synopsis

Bayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade. The free software program WinBUGS and its open-source sister OpenBugs is currently the only flexible and general-purpose program available with which the average ecologist can conduct standard and non-standard Bayesian statistics. Introduction to WINBUGS for Ecologists goes right to the heart of the matter by providing ecologists with a comprehensive, yet concise, guide to applying WinBUGS to the types of models that they use most often: linear (LM), generalized linear (GLM), linear mixed (LMM) and generalized linear mixed models (GLMM).

Introduction to WinBUGS for Ecologists combines the use of simulated data sets ''paired'' analyses using WinBUGS (in a Bayesian framework for analysis) and in R (in a frequentist mode of inference) and uses a very detailed step-by-step tutorial presentation style that really lets the reader repeat every step of the application of a given mode in their own research.

• 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

Content:
Front Matter, Pages i-ii
Copyright, Page iv
A Creed for Modeling, Page v
Foreword, Pages xi-xiv
Preface, Pages xv-xviii
Chapter 1 - Introduction, Pages 1-11
Chapter 2 - Introduction to the Bayesian Analysis of a Statistical Model, Pages 13-28
Chapter 3 - WinBUGS, Pages 29-32
Chapter 4 - A First Session in WinBUGS: The “Model of the Mean”, Pages 33-45
Chapter 5 - Running WinBUGS from R via R2WinBUGS, Pages 47-56
Chapter 6 - Key Components of (Generalized) Linear Models: Statistical Distributions and the Linear Predictor, Pages 57-89
Chapter 7 - t-Test: Equal and Unequal Variances, Pages 91-101
Chapter 8 - Normal Linear Regression, Pages 103-113
Chapter 9 - Normal One-Way ANOVA, Pages 115-127
Chapter 10 - Normal Two-Way ANOVA, Pages 129-139
Chapter 11 - General Linear Model (ANCOVA), Pages 141-150
Chapter 12 - Linear Mixed-Effects Model, Pages 151-166
Chapter 13 - Introduction to the Generalized Linear Model: Poisson “t-Test”, Pages 167-177
Chapter 14 - Overdispersion, Zero-Inflation, and Offsets in the GLM, Pages 179-191
Chapter 15 - Poisson ANCOVA, Pages 193-202
Chapter 16 - Poisson Mixed-Effects Model (Poisson GLMM), Pages 203-209
Chapter 17 - Binomial “t-Test”, Pages 211-217
Chapter 18 - Binomial Analysis of Covariance, Pages 219-228
Chapter 19 - Binomial Mixed-Effects Model (Binomial GLMM), Pages 229-236
Chapter 20 - Nonstandard GLMMs 1: Site-Occupancy Species Distribution Model, Pages 237-252
Chapter 21 - Nonstandard GLMMs 2: Binomial Mixture Model to Model Abundance, Pages 253-274
Chapter 22 - Conclusions, Pages 275-277
APPENDIX - A List of WinBUGS Tricks, Pages 279-284
References, Pages 285-289
Index, Pages 291-302