Capture-Recapture Models and Bayesian Sampling

Abstract : Capture-recapture models are widely used to estimate the unknown size of a closed population, N. A successful strategy for exploiting information about N in this setting is obtained through Bayesian modelling, as shown in Castledine (1981). However, direct Bayesian approaches are often cumbersome to implement in this setting. In this paper, we show how Bayesian sampling, using Gibbs sampling and data augmentation, is particularly well suited for use in a wide variety of capture-recapture models, including the multinomial and classical hypergeometric models. This approach can provide accurate approximations of posterior expressions, including the entire posterior distribution.

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