مقدمه‌ای بر Win: BUGS برای بوم‌شناسان. رویکرد بیزی به رگرسیون، آنووا، مدل‌های مختلط و تحلیل‌های مرتبط

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) 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 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. 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 - Written with ecological language and ecological examples - Companion Web Appendix that contains all code contained in the book, additional material (including more code and solutions to exercises) - Tutorial approach shows ecologists how to implement Bayesian analysis in practical problems that they face

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)

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 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 WinBUGS for Ecologists is an introduction to Bayesian statistical modeling, written for ecologists by an ecologist, using the widely available and free WinBUGS package. Examples are placed within a comprehensive and largely non-mathematical overview of linear, generalized linear (GLM), linear mixed and generalized linear mixed models (GLMM). This book will be interest to any quantitative scientist who uses regression-type models, especially ecologists, agronomists, geologists, epidemiologists, sociologists, and psychologists. --Book Jacket