A note on data augmentation and iterative simulation for survival rate estimation |
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Authors: | C Spyrou S P Brooks I C Olsen |
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Institution: | (1) The Statistical Laboratory, University of Cambridge, Wilberforce Road, Cambridge, CB3 0WB, UK;(2) Biometrics Department, Smerud Medical Research International AS, Drammensveien 41, 0271 Oslo, Norway |
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Abstract: | In this paper we examine the use of data augmentation techniques for simplifying iterative simulation in the context of both
Bayesian and classical statistical inference for survival rate estimation. We examine two distinct model families common in
population ecology to illustrate our ideas, ring-recovery models and capture–recapture models, and we present the computational
advantage of this approach. We discuss also the fact that problems associated with identifiability in the classical framework
can be overcome using data augmentation, but highlight the dangers in doing so under both inferential paradigms.
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Keywords: | Capture– recapture Ring-recovery EM algorithm Markov Chain Monte Carlo |
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