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Bayesian Population Analysis Using WinBUGS: A Hierarchical Perspective

Handbook / Manual

By: Marc Kery and Michael Schaub

535 pages, colour photos, colour & b/w illustrations, colour & b/w tables


Paperback | Oct 2011 | #192737 | ISBN-13: 9780123870209
Availability: Usually dispatched within 1 week Details
NHBS Price: £44.99 $55/€51 approx

About this book

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 the software package R. It 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.



1. Introduction
2. Brief introduction to Bayesian statistical modeling
3. Introduction to the generalized linear model: the simples model for count data
4. Introduction to random effects: conventional Poisson GLMM for count data
5. State-space models for population counts
6. Estimation of the size of a closed population from capture-recapture data
7. Estimation of survival from capture-recapture data using the Cormack-Jolly-Seber model
8. Estimation of survival using mark-recovery data
9. Estimation of survival and movement from capture-recapture data using multistate models
10. Estimation of survival, recruitment, and population size from capture-recapture data using the Jolly-Seber model
11. Estimation of demographic rates, population size, and projection matrices from multiple data types using integrated population models
12. Estimation of abundance from counts in metapopulation designs using the binomial mixture model
13. Estimation of occupancy and species distributions from detection/nondetection data in metapopulation designs using site-occupancy models
14. Concluding remarks

Appendix 1. A list of WinBUGS tricks
Appendix 2. Two further useful multistate capture-recapture models

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