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Bayesian analysis of one‐inflated models for elusive population size estimation
The identification and treatment of “one‐inflation” in estimating the size of an elusive population has received increasing attention in capture–recapture literature in recent years. The phenomenon occurs when the number of units captured exactly once clearly exceeds the expectation under a baseline...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9314905/ https://www.ncbi.nlm.nih.gov/pubmed/35534439 http://dx.doi.org/10.1002/bimj.202100187 |
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author | Tuoto, Tiziana Di Cecco, Davide Tancredi, Andrea |
author_facet | Tuoto, Tiziana Di Cecco, Davide Tancredi, Andrea |
author_sort | Tuoto, Tiziana |
collection | PubMed |
description | The identification and treatment of “one‐inflation” in estimating the size of an elusive population has received increasing attention in capture–recapture literature in recent years. The phenomenon occurs when the number of units captured exactly once clearly exceeds the expectation under a baseline count distribution. Ignoring one‐inflation has serious consequences for estimation of the population size, which can be drastically overestimated. In this paper we propose a Bayesian approach for Poisson, geometric, and negative binomial one‐inflated count distributions. Posterior inference for population size will be obtained applying a Gibbs sampler approach. We also provide a Bayesian approach to model selection. We illustrate the proposed methodology with simulated and real data and propose a new application in official statistics to estimate the number of people implicated in the exploitation of prostitution in Italy. |
format | Online Article Text |
id | pubmed-9314905 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93149052022-07-30 Bayesian analysis of one‐inflated models for elusive population size estimation Tuoto, Tiziana Di Cecco, Davide Tancredi, Andrea Biom J Advanced Data Analysis The identification and treatment of “one‐inflation” in estimating the size of an elusive population has received increasing attention in capture–recapture literature in recent years. The phenomenon occurs when the number of units captured exactly once clearly exceeds the expectation under a baseline count distribution. Ignoring one‐inflation has serious consequences for estimation of the population size, which can be drastically overestimated. In this paper we propose a Bayesian approach for Poisson, geometric, and negative binomial one‐inflated count distributions. Posterior inference for population size will be obtained applying a Gibbs sampler approach. We also provide a Bayesian approach to model selection. We illustrate the proposed methodology with simulated and real data and propose a new application in official statistics to estimate the number of people implicated in the exploitation of prostitution in Italy. John Wiley and Sons Inc. 2022-03-25 2022-06 /pmc/articles/PMC9314905/ /pubmed/35534439 http://dx.doi.org/10.1002/bimj.202100187 Text en © 2022 The Authors. Biometrical Journal published by Wiley‐VCH GmbH. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Advanced Data Analysis Tuoto, Tiziana Di Cecco, Davide Tancredi, Andrea Bayesian analysis of one‐inflated models for elusive population size estimation |
title | Bayesian analysis of one‐inflated models for elusive population size estimation |
title_full | Bayesian analysis of one‐inflated models for elusive population size estimation |
title_fullStr | Bayesian analysis of one‐inflated models for elusive population size estimation |
title_full_unstemmed | Bayesian analysis of one‐inflated models for elusive population size estimation |
title_short | Bayesian analysis of one‐inflated models for elusive population size estimation |
title_sort | bayesian analysis of one‐inflated models for elusive population size estimation |
topic | Advanced Data Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9314905/ https://www.ncbi.nlm.nih.gov/pubmed/35534439 http://dx.doi.org/10.1002/bimj.202100187 |
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