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Biometrika 2002 89(4):807-817; doi:10.1093/biomet/89.4.807
© 2002 by Biometrika Trust
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A new Bayesian method for nonparametric capture-recapture models in presence of heterogeneity

Luca Tardella1

1 Dipartimento di Statistica, Probabilità e Statistiche Applicate, Università "La Sapienza", 00185, Roma, Italy luca.tardella{at}uniroma1.it

The intrinsic heterogeneity of individuals is a potential source of bias in estimation procedures for capture-recapture models. To account for this heterogeneity in the model a hierarchical structure has been proposed whereby the probabilities that each animal is caught on a single occasion are modelled as independent draws from a common unknown distribution F.However, there is general agreement that modelling F by a simple parametric curve may lead to unsatisfactory results. Here we propose an alternative Bayesian approach that relies on a different parameterisation which imposes no assumption on the shape of F but drives the problem back to a finite-dimensional setting. Our approach avoids some identifiability issues related to such a recapture model while allowing for a formal Bayesian default analysis. Results of analyses of computer simulations and of real data show that the method performs well.

Key Words: Canonical moment; Capture-recapture; Closed population estimation; Default Bayesian analysis; Variable capture probability

Received March 2001. Revised January 2002


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