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A new mixture model for capture heterogeneity
Author(s) -
Morgan B. J. T.,
Ridout M. S.
Publication year - 2008
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2008.00620.x
Subject(s) - model selection , binomial (polynomial) , selection (genetic algorithm) , mixture model , computer science , binomial distribution , statistics , negative binomial distribution , econometrics , data mining , mathematics , machine learning , artificial intelligence , poisson distribution
Summary. We propose a mixture of binomial and beta–binomial distributions for estimating the size of closed populations. The new mixture model is applied to several real capture–recapture data sets and is shown to provide a convenient, objective framework for model selection. The new model is compared with three alternative models in a simulation study, and the results shed light on the general performance of models in this area. The new model provides a robust flexible analysis, which automatically deals with small capture probabilities.