Average Reviews:
(More customer reviews)This is a great book for using WinBUGS through R with the R library R2WinBUGS. It is actually also a pretty good book for performing classical linear modeling in R. All the analyses are performed in both R and WinBUGS. Much of the data is simulated but realistic, and the author shows you how he generated the data, which is also useful. Solutions to the exercises are available at the book's web site.
There is no reason to be an ecologist to use this book. The examples translate very well to other fields.
Despite this book being very useful to me, I gave it 4 instead of 5 stars for a few reasons. Very little attempt is made to explain the theory (to be fair, he says this at the outset, and it is a book about WinBUGS, not Bayesian statistics). The expected understanding of statistics and R is somewhat uneven throughout. For example, the author in one chapter shows you how to load libraries in R and other basic housekeeping tasks, but a few chapters later he shows more advanced model specification code in R's lm function without explaining it. Expect to spend some time in the R manual if you want to understand it all. Similarly, he repeatedly says that much of the statistics behind the code is too advanced for most ecologists, which might annoy me if I were an ecologist, but then he tends to assume a lot of the theoretical statistics is already well understood by the reader.
There is a quick introduction to Generalized Linear Models which I found helpful. Basically, this is a great practical book but you will need to look elsewhere for mathematical understanding. I like Peter Hoff's "A First Course in Bayesian Statistical Methods."
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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
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