By McCrea, Rachel S.
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Additional resources for Analysis of Capture-Recapture Data
A useful structure for models has been introduced by Otis et al. (1978): the binomial model with constant recapture probability is denoted by M0 ; model class Mt indicates that p varies with time; model class Mb indicates that there is a behavioural response to capture, and model class Mh denotes heterogeneity of capture, with diﬀerent values of p for diﬀerent individuals. Each of these classes contains several models, providing alternative descriptions of the variation in p. Combinations of the diﬀerent types of variation in capture probability result in 8 diﬀerent models/model classes in all.
5 Summary There is much current concern at the loss of biodiversity. We often study the behaviour of wild animals after giving them marks which identify them uniquely. It is usually assumed that marking does not aﬀect their survival, although there is some evidence to the contrary in certain special cases. Marked animals may be found dead, or seen again alive, providing information on demographic features such as mortality and movement. Estimates of mortality and of productivity are used in models of population dynamics, which can provide understanding of how populations change, and provide predictions of future behaviour.
In such cases an eﬃcient approach may be provided by using the theory of hidden Markov models; see Zucchini and MacDonald (1999). We shall encounter several applications of methods of hidden Markov models throughout the book. In other cases individual reencounter information can be reduced to sets of suﬃcient statistics, and then several of the likelihoods that we encounter are multinomial in form, or arise as products of multinomial distributions, where the models result from particular parameterisations of the multinomial cell probabilities.
Analysis of Capture-Recapture Data by McCrea, Rachel S.