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Accounting for non-independent detection when estimating abundance of organisms with a Bayesian approach
Article first published online: 26 APR 2011
© 2011 The Authors. Methods in Ecology and Evolution © 2011 British Ecological Society
Methods in Ecology and Evolution
Volume 2, Issue 6, pages 595–601, December 2011
How to Cite
Martin, J., Royle, J. A., Mackenzie, D. I., Edwards, H. H., Kéry, M. and Gardner, B. (2011), Accounting for non-independent detection when estimating abundance of organisms with a Bayesian approach. Methods in Ecology and Evolution, 2: 595–601. doi: 10.1111/j.2041-210X.2011.00113.x
- Issue published online: 5 DEC 2011
- Article first published online: 26 APR 2011
- Received 1 July 2010; accepted 14 March 2011 Handling Editor: Robert P. Freckleton
Appendix S1. Codes for running binomial mixture models on simulated data sets with R and WinBUGS.
Appendix S2. Codes for running beta-binomial mixture models on simulated data sets with R and WinBUGS.
Appendix S3. Estimation of the probability of a site being occupied conditional on manatees not being detected at the site (ψcondl).
Appendix S4. Codes for running beta-binomial mixture models, and accounting for variation in the size of sample units with R and WinBUGS.
Appendix S5. R and WinBUGS codes for running beta-binomial mixture models with abundance assumed to follow a zero-truncated Poisson distribution.
Appendix S6. Graphical representation of relative bias for each of the 16 estimators considered in Table 1.
Appendix S7. Posterior distribution for λ, p and ρ obtained by fitting the beta-binomial mixture models (with zero-truncated distribution for λ) to aerial survey data.
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