Literature DB >> 19035548

Population size estimation using individual level mixture models.

Daniel Manrique-Vallier1, Stephen E Fienberg.   

Abstract

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. ((c) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

Mesh:

Year:  2008        PMID: 19035548     DOI: 10.1002/bimj.200810448

Source DB:  PubMed          Journal:  Biom J        ISSN: 0323-3847            Impact factor:   2.207


  4 in total

1.  A spatial hierarchical model for integrating and bias-correcting data from passive and active disease surveillance systems.

Authors:  Xintong Li; Howard H Chang; Qu Cheng; Philip A Collender; Ting Li; Jinge He; Lance A Waller; Benjamin A Lopman; Justin V Remais
Journal:  Spat Spatiotemporal Epidemiol       Date:  2020-06-10

2.  Longitudinal Mixed Membership Trajectory Models for Disability Survey Data.

Authors:  Daniel Manrique-Vallier
Journal:  Ann Appl Stat       Date:  2014-12       Impact factor: 2.083

3.  Estimating Identification Disclosure Risk Using Mixed Membership Models.

Authors:  Daniel Manrique-Vallier; Jerome P Reiter
Journal:  J Am Stat Assoc       Date:  2012-12-01       Impact factor: 5.033

4.  Bayesian estimation of a cancer population by capture-recapture with individual capture heterogeneity and small sample.

Authors:  Laurent Bailly; Jean Pierre Daurès; Brigitte Dunais; Christian Pradier
Journal:  BMC Med Res Methodol       Date:  2015-04-24       Impact factor: 4.615

  4 in total

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