Introduction to WinBUGS for ecologists : a Bayesian Approach to Regression, ANOVA, Mixed Models and Related Analyses

Kery, Marc

ISBN 10: 0123786053 / ISBN 13: 9780123786050

Edité par Academic Press an Imprint of Elsevier, Burlington MA, 2010

A propos de cet article

xviii 302 pages. There is an ownership signature on the front end paper and front paste down and the glossy pages are very lightly damp affected, and I really mean lightly. A clean, unmarked and solid copy. "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. 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." (The publisher ).

N° de réf. du vendeur 019633

Détails bibliographiques

• Titre: Introduction to WinBUGS for ecologists : a Bayesian Approach to Regression, ANOVA, Mixed Models and Related Analyses
• Éditeur: Academic Press an Imprint of Elsevier, Burlington MA
• Date de parution: 2010
• Langue: anglais
• ISBN à 10 chiffres: 0123786053
• ISBN à 13 chiffres: 9780123786050
• Reliure: Soft cover
• Édition: First Edition
• État de l'article: Near Fine
• Catalogues du vendeur:
  • Environmental Science

A propos de ce titre

Synopsis

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 distributions: 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.

À propos de l?auteur

Dr. Marc works as a senior scientist at the Swiss Ornithological Institute, Seerose 1, 6204 Sempach, Switzerland. This is a non-profit NGO with about 160 employees dedicated primarily to bird research, monitoring, and conservation. Marc was trained as a plant population ecologist at the Swiss Universities of Basel and Zuerich. After a 2-year postdoc at the (then) USGS Patuxent Wildlife Center in Laurel, MD. During the last 20 years he has worked at the interface between population ecology, biodiversity monitoring, wildlife management, and statistics. He has published more than 100 peer-reviewed journal articles and five textbooks on applied statistical modeling. He has also been very active in teaching fellow biologists and wildlife managers the concepts and tools of modern statistical analysis in their fields in workshops all over the world, something which goes together with his books, which target the same audiences.