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By Adrian E. Raftery (Editor), Martin A. Tanner (Editor), Martin T. Wells (Editor)

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And Pollock, H. (1998), “Multiyear Tagging Studies Incorporating Fishing Effort Data,” Canadian Journal of Fisheries and Aquatic Science, 55, 1466– 1476. Huggins, R. M. (1989), “On the Statistical Analysis of Capture Experiments,” Biometrika, 76, 133–140. Jolly, G. M. (1965), “Explicit Estimates From Capture–Recapture Data With Both Death and Immigration— Stochastic Model,” Biometrika, 52, 225–247. , Burnham, K. , and Anderson, D. R. (1992), “Modelling Survival and Testing Biological Hypotheses Using Marked Animals: A Unified Approach with Case Studies,” Ecological Monographs, 62, 67–118.

The heterogeneity models that use a distribution of capture probabilities have caused theoretical difficulty for statisticians. An early ad hoc approach based on the “jackknife” method (Burnham and Overton 1978) proved quite useful. , Lee and Chao 1994). Others have suggested using log-linear models (Cormack 1989). Maximum likelihood estimation, where the heterogeneity is modeled as a finite mixture distribution, usually with two or three support points, is a recent development (Norris and Pollock 1996a; Pledger 2000).

The hexagonal design requires fewer sampling sites than a square or triangular design to cover the same area, but does not take into account spatial covariance heterogeneity or temporal nonstationarity. The covariance mapping technique mentioned in Section 3 can be used to deal with spatial heterogeneity, by implementing a spatial design in the transformed space. , Caselton, Kan, and Zidek 1992; Guttorp, Le, Sampson, and Zidek 1993) have developed an approach to network design that can deal with heterogeneous random fields.

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