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Can I read Introduction to Win: BUGS for Ecologists. A Bayesian Approach to Regression, Anova, Mixed Models, and Related Analyses on EtoBox?
Introduction to Win: BUGS for Ecologists. A Bayesian Approach to Regression, Anova, Mixed Models, and Related Analyses by Marc Kéry (Auth.) is a nonfiction available to read on EtoBox.
What is Introduction to Win: BUGS for Ecologists. A Bayesian Approach to Regression, Anova, Mixed Models, and Related Analyses about?
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
Who reads Introduction to Win: BUGS for Ecologists. A Bayesian Approach to Regression, Anova, Mixed Models, and Related Analyses?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Marc Kéry (Auth.)
- Publisher
- Academic Press, Incorporated
- Published
- 2010
- Language
- EN
- ISBN
- 9781282755666
- Category
- nonfiction
- Subjects
- Science, Mathematics, Biology
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