Introduction to Hierarchical Bayesian Modeling for Ecological Data
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$89.95$80.96 - Hardback: 412 pages
- Published: July 2012
- ISBN: 978-1-58488-919-9
- Publisher: Chapman and Hall/CRC
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- By Eric Parent, and Etienne Rivot.
- Series Edited by Marcel F. Neuts, Nicholas P. Jewell, Anant Kshirsagar, Aman Ullah, Arjun K. Gupta, William R. Schucany and Edward G. Schilling.
Series: Chapman & Hall/CRC Applied Environmental Statistics.
Bayesian statistics are becoming the contemporary standard for treating ecological data. This book is designed for readers who are interested in the quantitative analysis of environmental data yet reluctant to apply ready-made technical recipes without understanding how and why they work. Mainly based on real case studies from fish population investigations, it highlights up-to-date ecological issues, including biodiversity, population behavior, and uncertainty, and shows how they could be revisited by using Bayesian modeling techniques. The text encourages readers to deal with advanced ecological issues in practice and to implement models of their own.
Table of Contents
Introduction. The Elementary Beta-Binomial Model for a Capture-Marked Experiment. The Normal Model: Does the Fish Farm Pollution Influence Juvenile Growth?. Playing with the Beta-Binomial Model. Introducing Explanatory Variables. Borrowing Strength from Similar Units?. Observations Errors. More than One Component Data. Dynamics. Cocktail Models for Combining Various Sources of Information. Planification/Decision.




