1. An evaluation of the Bayesian approach to fitting the N-mixture model for use with pseudo-replicated count data
- Author
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S. Liang, Brian R. Gray, and S. G. Toribio
- Subjects
Statistics and Probability ,Applied Mathematics ,Bayesian probability ,Mixture model ,Empirical probability ,Bayesian statistics ,Modeling and Simulation ,Statistics ,Bayesian hierarchical modeling ,Statistics, Probability and Uncertainty ,Bayesian linear regression ,Bayesian average ,Mathematics ,Count data - Abstract
The N-mixture model proposed by Royle in 2004 may be used to approximate the abundance and detection probability of animal species in a given region. In 2006, Royle and Dorazio discussed the advantages of using a Bayesian approach in modelling animal abundance and occurrence using a hierarchical N-mixture model. N-mixture models assume replication on sampling sites, an assumption that may be violated when the site is not closed to changes in abundance during the survey period or when nominal replicates are defined spatially. In this paper, we studied the robustness of a Bayesian approach to fitting the N-mixture model for pseudo-replicated count data. Our simulation results showed that the Bayesian estimates for abundance and detection probability are slightly biased when the actual detection probability is small and are sensitive to the presence of extra variability within local sites.
- Published
- 2012