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Continuous-time capture-recapture in closed populations
Matthew R Schofield1, Richard J Barker1, Nicholas Gelling1
1Department of Mathematics and Statistics, University of Otago, New Zealand.
Abstract:
The standard approach to fitting capture-recapture data collected in continuous time involves arbitrarily forcing the data into a series of distinct discrete capture sessions. We show how continuous-time models can be fitted as easily as discrete-time alternatives. The likelihood is factored so that efficient Markov chain Monte Carlo algorithms can be implemented for Bayesian estimation, available online in the R package ctime. We consider goodness-of-fit tests for behavior and heterogeneity effects as well as implementing models that allow for such effects.
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