%0 Journal Article %1 poole_bayesian_2002 %A Poole, David %D 2002 %J Journal of Agricultural, Biological, and Environmental Statistics %K Bayesian capture-recapture, carlo carlo, chain, data, fulmar inference, likelihood, markov maximum missing monte petrels, survival %N 2 %P 264--276 %T Bayesian Estimation of Survival From Mark – Recapture Data %V 7 %X An understanding of survival patterns is a fundamental component of animal population biology. Mark–recapture models are often used in the estimation of animal survival rates. Maximum likelihood estimation, via either analytic solution or numerical approx- imation, has typically been used for inference in these models throughout the literature. In this article, a Bayesian approach is outlined and an easily applicable implementation via Markov chain Monte Carlo is described. The method is illustrated using 13 years of mark–recapture data for fulmar petrels on an island in Orkney. Point estimates of survival are similar to the maximum likelihood estimates (MLEs), but the posterior variances are smaller than the corresponding asymptotic variances of the MLEs. The Bayesian approach yieldspoint estimates of 0.9328 for the average annual survival probability and 14.37 years for the expected lifetime of the fulmar petrels. A simple modication that accounts formissing data is also described. The approach is easier to apply than augmentation methods in this case, and simulations indicate that the performanceof the estimators is not signicantly diminished by the missing data.

@article{poole_bayesian_2002, abstract = {An understanding of survival patterns is a fundamental component of animal population biology. Mark–recapture models are often used in the estimation of animal survival rates. Maximum likelihood estimation, via either analytic solution or numerical approx- imation, has typically been used for inference in these models throughout the literature. In this article, a Bayesian approach is outlined and an easily applicable implementation via Markov chain Monte Carlo is described. The method is illustrated using 13 years of mark–recapture data for fulmar petrels on an island in Orkney. Point estimates of survival are similar to the maximum likelihood estimates (MLEs), but the posterior variances are smaller than the corresponding asymptotic variances of the MLEs. The Bayesian approach yieldspoint estimates of 0.9328 for the average annual survival probability and 14.37 years for the expected lifetime of the fulmar petrels. A simple modication that accounts formissing data is also described. The approach is easier to apply than augmentation methods in this case, and simulations indicate that the performanceof the estimators is not signicantly diminished by the missing data.}, added-at = {2017-01-09T13:57:26.000+0100}, author = {Poole, David}, biburl = {https://www.bibsonomy.org/bibtex/25618b0c03eee11b1cdd61490ae23d9fb/yourwelcome}, interhash = {6a86d082824099bd56c2d9ab0e4eb308}, intrahash = {5618b0c03eee11b1cdd61490ae23d9fb}, journal = {Journal of Agricultural, Biological, and Environmental Statistics}, keywords = {Bayesian capture-recapture, carlo carlo, chain, data, fulmar inference, likelihood, markov maximum missing monte petrels, survival}, number = 2, pages = {264--276}, timestamp = {2017-01-09T14:01:11.000+0100}, title = {Bayesian {Estimation} of {Survival} {From} {Mark} – {Recapture} {Data}}, volume = 7, year = 2002 }