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Bayesian Methods for Ecology, by Michael A. McCarthy
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The interest in using Bayesian methods in ecology is increasing, however many ecologists have difficulty with conducting the required analyses. McCarthy bridges that gap, using a clear and accessible style. The text also incorporates case studies to demonstrate mark-recapture analysis, development of population models and the use of subjective judgement. The advantages of Bayesian methods, are also described here, for example, the incorporation of any relevant prior information and the ability to assess the evidence in favour of competing hypotheses. Free software is available as well as an accompanying web-site containing the data files and WinBUGS codes. Bayesian Methods for Ecology will appeal to academic researchers, upper undergraduate and graduate students of Ecology.
- Sales Rank: #1239055 in Books
- Brand: Brand: Cambridge University Press
- Published on: 2007-05-14
- Released on: 2007-05-10
- Original language: English
- Number of items: 1
- Dimensions: 8.98" h x .67" w x 5.98" l, 1.05 pounds
- Binding: Paperback
- 312 pages
- Used Book in Good Condition
Review
"[This book] will advance any ecologists' understanding of Bayesian statistics. ... the many diverse examples, which are the book's greatest strength, make the topic very approachable, even for people with moderate understanding of statistical theory. ... I therefore would highly recommend it to any ecologist interested in learning more about Bayesian statistics, and especially to those who want to learn to run Bayesian analyses in Win BUGS." - Tabitha Graves, Ecology
About the Author
Michael A. McCarthy is Senior Ecologist at the Royal Botanical Gardens, Melbourne and Senior Fellow in the School of Botany at the University of Melbourne.
Most helpful customer reviews
0 of 0 people found the following review helpful.
Excellent book for biologists/ecologists interested in bayesian statistics.
By Michelle L Johnston
The authors of this book give an excellent overview with examples of Bayesian statistics from an ecologists' point of view. They assume that you have no experience in Bayesian stats but have a basic background in regular "frequentist" statistics (i.e. hypothesis testing, t-tests, anova, etc). Its really well written and the examples are very valuable in learning the program OpenBUGS and in understanding the concepts. I would recommend for anyone interested in learning about Bayesian statstics, from a general interest to someone using them in the phd dissertation.
16 of 16 people found the following review helpful.
Good BUGS cookbook
By J. Byrnes
I recently used this book for a class, and found it a good introduction for those already well familiar with classical frequentist techniques in ecology. It provides good cookbook recipes for doing an ANOVA, regression, etc with BUGS. The first chapter also cites some good reasons as to WHY one should use Bayes when they have prior information over other techniques. This was NOT however, a book that was particularly useful for those who want a thorough introduction to Bayes, warts and all, as well as giving one a real thorough understanding of Hierarchical modeling, which is arguably where Bayes can see it's best applications, particularly in ecology. The class as a whole felt like the book needs more thorough examples, more explanations of the WHYs, as well as the potential pitfalls, how to find problems with your models, as well as some applied problem sets. We also used Gelman and Hill's book, which has been excellent as a more thorough introduction, even if it is in the social sciences, and I have high hopes for James Clark's new book, although I have not seen a copy yet.
1 of 1 people found the following review helpful.
Great for learning WinBugs
By Martin L. Jones
This book is a great little book for learning some code for programming in WinBUGS. I used it to supplement a course in Bayesian Data Analysis.
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