ABSTRACT
This chapter argues that both issues, of uncertainty of detection and uncertainty of state identification, are present in the data at hand. It provides to a capture–recapture setting where the classic assumption of absence of error in the unit’s identification is relaxed. There are examples of capture–recapture models with a different number of modalities for the observed and the latent variables, namely in multistate models, to account for uncertainty in state assignment. Model selection is a crucial point in–recapture, as often the estimates of the population size are very sensitive to small changes in the choice of the parameters. Failing to model either list dependencies or heterogeneity in individual capture probabilities usually leads to biased estimates of the population size. Failing to model either list dependencies or heterogeneity in individual capture probabilities usually leads to biased estimates of the population size.
