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Bayesian Population Analysis using WinBUGS: A hierarchical perspective [Paperback]

Marc Kery , Michael Schaub
5.0 out of 5 stars  See all reviews (3 customer reviews)

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Book Description

October 12, 2011 0123870208 978-0123870209 1

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.

  • Comprehensive and richly-commented examples illustrate a wide range of models that are most relevant to the research of a modern population ecologist.
  • All WinBUGS/OpenBUGS analyses are completely integrated in software R.
  • Includes complete documentation of all R and WinBUGS code required to conduct analyses and shows all the necessary steps from having the data in a text file out of Excel to interpreting and processing the output from WinBUGS in R.

Frequently Bought Together

Bayesian Population Analysis using WinBUGS: A hierarchical perspective + Introduction to WinBUGS for Ecologists: Bayesian approach to regression, ANOVA, mixed models and related analyses + Hierarchical Modeling and Inference in Ecology: The Analysis of Data from Populations, Metapopulations and Communities
Price for all three: $175.44

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Editorial Reviews

From the Back Cover

Bayesian Population Analysis using WinBUGS is an introduction to the analysis of distribution, abundance, and population dynamics of animals and plants using hierarchical models implemented in the leading Bayesian software WinBUGS. It will be of interest to quantitative scientists working in the fields of population ecology, conservation biology, evolutionary biology, population management, disease ecology, fisheries or wildlife biology. The accessible text is ideal for self-study and advanced graduate-level courses.

This book:

  • Is a statistical modeling book written by ecologists for ecologists
  • Contains analyses of simulated data, along with fully commented R code for the generation of these data sets, as well as analyses of real data
  • Fully integrates with program R-all analyses are conducted by calling WinBUGS from R
  • Illustrates the tremendous modeling freedom given to ecologists when using the simple and flexible BUGS language

Marc Kéry and Michael Schaub are population ecologists with the Swiss Ornithological Institute. Together, they have authored over 120 peer-reviewed journal articles on a wide range of topics, including the analysis of large-scale monitoring programs, demographic population analyses, experimental design for animal and plant surveys, and the population ecology of rare species, as well as Introduction to WinBUGS for Ecologists (Academic Press, 2010).


Product Details

  • Paperback: 554 pages
  • Publisher: Academic Press; 1 edition (October 12, 2011)
  • Language: English
  • ISBN-10: 0123870208
  • ISBN-13: 978-0123870209
  • Product Dimensions: 6 x 1 x 9 inches
  • Shipping Weight: 2 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #106,990 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews
2 of 2 people found the following review helpful
5.0 out of 5 stars Excellent book for learning Bayesian analysis October 17, 2011
By efz
Format:Paperback
I highly recommend this book if you are interested in learning Bayesian analysis and/or Winbugs. Similar to Kery's first book, Introduction to Winbugs for Ecologists, this book is a gentle introduction to common (yet advanced!) modeling techniques written for those who are new to modeling and statistics. The introductory chapters are especially useful for understanding how Bayesian analysis and model based statistics can be a more intuitive framework compared to traditional statistics that are taught in class. What makes this book so valuable is that the authors spend each chapter building up from the simplest form of a model to its most complex iteration. Because of this, it's actually been possible to figure out how to analyze my own data!
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5.0 out of 5 stars Both Kery's books are excellent May 1, 2012
By Andy
Format:Paperback|Amazon Verified Purchase
I don't normally write reviews for books on Amazon but having purchased both of Kery's books on Bayesian analysis and having read several others I have to say these two books are the best for anyone working on wildlife and ecology. They lead you through the basics of running analyses and yet get to some pretty complex analyses in an easily understandable way. For an ecologist trying to teach themselves bayesian statistics these are excellent. The Bayesian population analysis using Winbugs book take you through bayesian analyses of estimating population abundance as well as determination of population dynamics such as birth and death rates using freely available Winbugs and R software. It shows you how to analyse hierarchical models that factor in detection probability in the observation process in winbugs in a much more easily understandable way than Andy Royle's book. Both Kery's books were definitely worth buying and I keep returning to them
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5.0 out of 5 stars Essential March 12, 2012
Format:Paperback|Amazon Verified Purchase
This book covers examples of fairly complex models (at least for the average ecologist), and ways to analyze them in a Bayesian framework. I found this particularly useful for mark-recapture analysis. Full code is provided for every example, which I found could be easily modified to fit my own data in several cases (although I still had to do some heavy lifting in many instances). I think this book, together with Royle and Dorazio, and McCarthy, is a nice addition to the library of the ecologist interested in implementing Bayesian analysis, but who may not be at the level of coding a Jolly-Seber model (insert other examples here) unassisted. The chapter on integrated population models alone made this book worth the money for me (I haven't seen this type of modeling presented more clearly anywhere else). Well done, and thanks to the authors for their contribution to ecologists.
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