Marc Kery (Senior Scientist, Swiss Ornithological Institute, Basel,, Kenneth F. Kellner (Michigan State Un Assistant Research Professor

Applied Statistical Modelling for Ecologists

A Practical Guide to Bayesian and Likelihood Inference Using R, JAGS, NIMBLE, Stan and TMB

• Broschiertes Buch

Produktbeschreibung

Applied Statistical Modelling for Ecologists provides a gentle introduction to the essential models of applied statistics: linear models, generalized linear models, mixed and hierarchical models. All models are fit with both a likelihood and a Bayesian approach, using several powerful software packages widely used in research publications: JAGS, NIMBLE, Stan, and TMB. In addition, the foundational method of maximum likelihood is explained in a manner that ecologists can really understand. This book is the successor of the widely used Introduction to WinBUGS for Ecologists (Kéry, Academic Press, 2010). Like its parent, it is extremely effective for both classroom use and self-study, allowing students and researchers alike to quickly learn, understand, and carry out a very wide range of statistical modelling tasks. The examples in Applied Statistical Modelling for Ecologists come from ecology and the environmental sciences, but the underlying statistical models are very widely used by scientists across many disciplines. This book will be useful for anybody who needs to learn and quickly become proficient in statistical modelling, with either a likelihood or a Bayesian focus, and in the model-fitting engines covered, including the three latest packages NIMBLE, Stan, and TMB.

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Produktdetails

• Verlag: Elsevier - Health Sciences Division
• Seitenzahl: 550
• Erscheinungstermin: 18. Juli 2024
• Englisch
• Abmessung: 233mm x 187mm x 27mm
• Gewicht: 1096g
• ISBN-13: 9780443137150
• ISBN-10: 0443137153
• Artikelnr.: 68169314

Autorenporträt

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.

Inhaltsangabe

1. Introduction 2. Introduction to statistical inference 3. Linear
regression models and their extensions to generalized linear, hierarchical
and integrated models 4. Introduction to general-purpose model-fitting
engines and the model of the mean 5. Simple linear regression with Normal
errors 6. Comparison of two groups 7. Comparisons among multiple groups 8.
Comparisons in two classifications or with two categorical covariates 9.
General linear model with continuous and categorical explanatory variables
10. Linear mixed-effects model 11. Introduction to the Generalized linear
model (GLM): Comparing two groups in a Poisson regression 12.
Overdispersion, zero-inflation and offsets in a GLM 13. Poisson regression
with both continuous and categorical explanatory variables 14. Poisson
mixed-effects model or Poisson GLMM 15. Comparing two groups in a Binomial
regression 16. Binomial GLM with both continuous and categorical
explanatory variables 17. Binomial mixed-effects model or Binomial GLMM 18.
Model building, model checking and model selection 19. General hierarchical
models: Site-occupancy species distribution model (SDM) 20. Integrated
models 21. Conclusion