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Bayesian Inference for Small‐Sample Capture‐Recapture Data
Author(s) -
ChavezDemoulin V.
Publication year - 1999
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.1999.00727.x
Subject(s) - mark and recapture , laplace's method , bayes' theorem , statistics , bayesian probability , inference , bayesian inference , population , sampling (signal processing) , computer science , mathematics , artificial intelligence , demography , sociology , computer vision , filter (signal processing)
Summary. We consider data on the survival of a population of Cephalorhynchus hectori , Hector's dolphins, in a marine area of New Zealand. To estimate survival probabilities of animal populations, a multiple capture‐recapture sampling scheme can be used. In this paper, we propose a practical methodology to derive approximations to posterior distributions based on Laplace methods. We show how to calculate Bayes estimates and credible intervals in this setting.