Introduction to WinBUGS for Ecologists

Marc Kéry

ISBN 10: 0123786053 / ISBN 13: 9780123786050

Edité par Elsevier Science Publishing Co Inc, 2010

A propos de cet article

2010. 1st Edition. Paperback. 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. Num Pages: 320 pages, Illustrated. BIC Classification: PBT; PSAF. Category: (P) Professional & Vocational. Dimension: 229 x 152 x 20. Weight in Grams: 542. . . . . . Books ship from the US and Ireland.

N° de réf. du vendeur V9780123786050

Détails bibliographiques

• Titre: Introduction to WinBUGS for Ecologists
• Éditeur: Elsevier Science Publishing Co Inc
• Date de parution: 2010
• Langue: anglais
• ISBN à 10 chiffres: 0123786053
• ISBN à 13 chiffres: 9780123786050
• Reliure: Couverture souple
• État de l'article: New

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.