Premium
Population Size Estimation Using Individual Level Mixture Models
Author(s) -
ManriqueVallier Daniel,
Fienberg Stephen E.
Publication year - 2008
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.200810448
Subject(s) - bayes' theorem , population , construct (python library) , mathematics , statistics , homogeneous , estimation , markov chain monte carlo , cluster analysis , mixture model , econometrics , hierarchical clustering , mark and recapture , computer science , bayesian probability , demography , combinatorics , economics , management , sociology , programming language
We revisit the heterogeneous closed population multiple recapture problem, modeling individual‐level heterogeneity using the Grade of Membership model (Woodbury et al., 1978). This strategy allows us to postulate the existence of homogeneous latent “ideal” or “pure” classes within the population, and construct a soft clustering of the individuals, where each one is allowed partial or mixed membership in all of these classes. We propose a full hierarchical Bayes specification and a MCMC algorithm to obtain samples from the posterior distribution. We apply the method to simulated data and to three real life examples. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)