Introduction to WinBUGS for Ecologists book cover

Introduction to WinBUGS for Ecologists

Bayesian approach to regression, ANOVA, mixed models and related analyses

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.

Audience
Ecologists, upper-level graduate and graduate ecology students.

Paperback, 320 Pages

Published: June 2010

Imprint: Academic Press

ISBN: 978-0-12-378605-0

Reviews

  • "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


Contents

  • Chapter One: Introduction

    Chapter Two: Principles of Bayesian Statistics

    Chapter Three: WinBUGS (and a little bit on R)

    Chapter Four: A First Session in WinBUGS: The "Model of the Mean"

    Chapter Five: Running WinBUGS from R via R2WinBUGS

    Chapter Six: Key Components of Generalized Linear Models: Statistical Distributions and the Linear Predictor

    Chapter Seven: T-Test: Equal and Unequal Variance

    Chapter Eight: Normal Linear Regression

    Chapter Nine: Normal One-Way ANOVA

    Chapter Ten: Interaction

    Chapter Eleven: General Linear Model (ANCOVA)

    Chapter Twelve: Linear Mixed-Effects Model

    Chapter Thirteen: Introduction to the Generalized Linear Model (GLM): Poisson T-Test

    Chapter Fourteen: Over dispersion and Offsets in the GLM

    Chapter Fifteen: Poisson ANCOVA

    Chapter Sixteen: Poisson Mixed-Effects Model (Poisson GLMM)

    Chapter Seventeen: Binomial T-Test

    Chapter Eighteen: Binomial ANCOVA

    Chapter Nineteen: Binomial Mixed-Effects Model (Binomial GLMM)

    Chapter Twenty: Non-standard GLMMs 1: Site Occupancy Distribution Model

    Chapter Twenty-One: Non-standard GLMMs 2: Binomial Mixture Model for the Modeling of True Abundance

    Chapter Twenty-Two: Conclusion and Outlook

    Acknowledgements

    References

    Solutions to Exercises

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