Heterogeneity Closed Captures

Two different data types are available for modeling individual heterogeneity with closed capture data. The first data type is the simpliest, and can be thought of as only allowing model Mh. That is, following Norris and Pollock (1995) and Pledger (1998, 2000), a mixture of capture probabilities is allowed for each animal. For the simple heterogeneity model (Mh), the only parameter allowed is the initial capture probability, p, assumed to be the same for each occasion, with no differences for recaptures (c). For the complex heterogeneity model (Mtbh), the p's and c's for each mixture are available to be modeled. The drawback of using this model is that the modeling of the p's and c's must be such that estimates of N are provided.

Both of the simple and complex heterogeneity models are also available as Huggins (1989, 1991) versions, where the population size (N) is conditioned out of the likelihood and the population estimate is obtained as a derived parameter.

Further, both the simple and complex heterogeneity models are also available for the mis-identification closed capture models. However, incorporation of both mis-identificaiton and heterogeneity typically leads to inconclusive results, in that mis-identification is somewhat confounded with heterogeneity.