Bayesian population analysis using WinBUGS : a hierarchical perspective

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Bibliographic Information

Bayesian population analysis using WinBUGS : a hierarchical perspective

[by] Marc Kéry and Michael Schaub ; foreword by Steven R. Beissinger

Academic Press, 2012

  • : pbk

Available at  / 15 libraries

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Includes bibliographical references and index

Description and Table of Contents

Description

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.

Table of Contents

1. Introduction 2. Very brief introduction to Bayesian statistical modeling 3. Introduction to the generalized linear model (GLM): The simplest model for count data 4. Introduction to random effects: The conventional Poisson GLMM for count data 5. State-space models 6. Estimation of population size 7. Estimation of survival probabilities using capture-recapture data 8. Estimation of survival probabilities using mark-recovery data 9. Multistate capture-recapture models 10. Estimation of survival and recruitment using the Jolly-Seber model 11. Integrated population models 12. Metapopulation modeling of abundance using hierarchical Poisson regression 13. Metapopulation modeling of species distributions using hierarchical logistic regression 14. Concluding remarks

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