Combined Data Models
In previous chapters, we have considered three methods of obtaining recapture data: dead recoveries, resightings, and live recaptures. As the models for all three methods have a similar structure, except for different definitions of the population parameters, it is not surprising we can combine three different pairs of methods or all three into combined models. In this chapter, all four possible models are considered in detail by redefining the parameters. Ken Burnham, in 1993, combined live recaptures with dead recoveries and incorporated either permanent immigration or random immigration into the model. Goodness-of-fit tests are given, and we describe extensions to the model to allow for such things as age, time, age plus time, delayed recoveries, and covariates (including missing values). Bayesian models, hidden Markov models, the utilization of radio tags, and continuous models that focus on instantaneous natural and fishing mortality rates are described in considerable detail. Another combined pair of methods uses recaptures and sightings with losses that provide some dead individuals. Richard Barker in 1997 developed such a complex model particularly aimed at fish angling. Random emigration was included as a special case along with goodness-of-fit tests for it. Finally, we consider the model combining all three methods of data collection, which can incorporate various forms of migration.