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Bayesian Methods for Ecology - Tapa dura

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9780521850575: Bayesian Methods for Ecology
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Statistical analysis of data is fundamentally important in ecology but most ecologists have difficulty with conducting analyses. McCarthy describes how to use Bayesian methods to analyse a wide range of data and models in ecology. This accessible text will appeal to academic researchers, upper undergraduate and graduate students of Ecology.

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"[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
Reseña del editor:
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.

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  • EditorialCambridge University Press
  • Año de publicación2007
  • ISBN 10 0521850576
  • ISBN 13 9780521850575
  • EncuadernaciónTapa dura
  • Número de edición1
  • Número de páginas310
  • Valoración
    • 3,43
      7 calificaciones proporcionadas por Goodreads

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9780521615594: Bayesian Methods for Ecology Paperback

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ISBN 10:  0521615593 ISBN 13:  9780521615594
Editorial: Cambridge University Press, 2007
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