# Introduction to WinBUGS for ecologists : a Bayesian approach to regression, ANOVA, mixed models, and related analyses / Marc Kéry, Swiss Ornithological Institute, 6204 Sempach, Switzerland.

##### By: Kéry, Marc [author.]

Material type: TextPublisher: Burlington, Massachusetts : Elsevier/Academic Press, 2010Edition: First editionDescription: 1 online resource (xviii, 302 pages) : illustrations (some color)Content type: text Media type: computer Carrier type: online resourceISBN: 0123786061; 9780123786067; 9781282755666; 1282755668; 9786612755668; 6612755660Subject(s): WinBUGS | WinBUGS | Biometry -- Data processing | SCIENCE -- Environmental Science (see also Chemistry -- Environmental) | NATURE -- Ecosystems & Habitats -- Wilderness | NATURE -- Ecology | SCIENCE -- Life Sciences -- Ecology | Biometry -- Data processing | statistische analyse | statistical analysis | ecologie | ecology | biostatistiek | biostatistics | toegepaste statistiek | applied statistics | bayesiaanse theorie | bayesian theory | studieboeken | textbooks | Applied Statistics | Ecology (General) | Toegepaste statistiek | Ecologie (algemeen)Genre/Form: Electronic books. | Electronic books. Additional physical formats: Print version:: Introduction to WinBUGS for ecologists.DDC classification: 577.01/5118 LOC classification: QH323.5 | .K47 2010Online resources: Click here to access onlineItem type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Includes bibliographical references (pages 285-289) and index.

Online resource; title from e-book title screen (EBL platform, viewed May 16, 2016).

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.

Introduction to the Bayesian Analysis of a Statistical Model -- WinBUGS -- A First Session in WinBUGS: The "Model of the Mean" -- Running WinBUGS from R via R2WinBUGS -- Key Components of (Generalized) Linear Models: Statistical Distributions and the Linear Predictor -- t-Test: Equal and Unequal Variances -- Normal Linear Regression -- Normal One-Way ANOVA -- Normal Two-Way ANOVA -- General Linear Model (ANCOVA) -- Linear Mixed-Effects Model -- Introduction to the Generalized Linear Model: Poisson "t-test" -- Overdispersion, Zero-Inflation, and Offsets in the GLM -- Poisson ANCOVA -- Poisson Mixed-Effects Model (Poisson GLMM) -- Binomial "t-Test" -- Binomial Analysis of Covariance -- Binomial Mixed-Effects Model (Binomial GLMM) -- Nonstandard GLMMs 1: Site-Occupancy Species Distribution Model -- Nonstandard GLMMs 2: Binomial Mixture Model to Model Abundance.

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