Books  Ecological & Biological Sciences  Data Analysis & Modelling  Data Analysis & Statistics 

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

By: Marc Kéry

302 pages, Figs

Academic Press

Paperback | Jul 2010 | #186645 | ISBN-13: 9780123786050
Availability: Usually dispatched within 1-2 weeks Details
NHBS Price: £40.99 $53/€46 approx

About this book

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 their own standard and non-standard Bayesian statistics.

This book 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).


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



Solutions to Exercises

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