Abstract

We consider capture-recapture studies where release and recapture data are available from each of a number of strata on every capture occasion. Strata may, for example, be geographic locations or physiological states. Movement of animals among strata occurs with unknown probabilities, and estimation of these unknown transition probabilities is the objective. We describe a computer routine for carrying out the analysis under a model that assumes Markovian transitions and under reducedparameter versions of this model. We also introduce models that relax the Markovian assumption and allow memory to operate (i.e., allow dependence of the transition probabilities on the previous state). For these models, we suggest an analysis based on a conditional likelihood approach. Methods are illustrated with data from a large study on Canada geese (Branta canadensis) banded in three geographic regions. The assumption of Markovian transitions is rejected convincingly for these data, emphasizing the importance of the more general models that allow memory.

Keywords

Mark and recaptureMarkov processStatistical physicsComputer scienceEstimationMarkov chainEconometricsStatisticsMathematicsPhysicsDemography

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Publication Info

Year
1993
Type
article
Volume
49
Issue
4
Pages
1173-1173
Citations
741
Access
Closed

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Cavell Brownie, James E. Hines, James D. Nichols et al. (1993). Capture-Recapture Studies for Multiple Strata Including Non-Markovian Transitions. Biometrics , 49 (4) , 1173-1173. https://doi.org/10.2307/2532259

Identifiers

DOI
10.2307/2532259