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On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods

One‐inflation in zero‐truncated count data has recently found considerable attention. There are currently two views in the literature. In the first approach, the untruncated model is considered as one‐inflated whereas in the second approach the truncated model is viewed as one‐inflated. Here, we sho...

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Autor principal: Böhning, Dankmar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10087693/
https://www.ncbi.nlm.nih.gov/pubmed/35971027
http://dx.doi.org/10.1002/bimj.202100343
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author Böhning, Dankmar
author_facet Böhning, Dankmar
author_sort Böhning, Dankmar
collection PubMed
description One‐inflation in zero‐truncated count data has recently found considerable attention. There are currently two views in the literature. In the first approach, the untruncated model is considered as one‐inflated whereas in the second approach the truncated model is viewed as one‐inflated. Here, we show that both models have identical model spaces as well as identical maximum likelihoods. Consequences of population size estimation are illuminated, and the findings are illustrated at hand of two case studies.
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spelling pubmed-100876932023-04-12 On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods Böhning, Dankmar Biom J Methods for Count Data One‐inflation in zero‐truncated count data has recently found considerable attention. There are currently two views in the literature. In the first approach, the untruncated model is considered as one‐inflated whereas in the second approach the truncated model is viewed as one‐inflated. Here, we show that both models have identical model spaces as well as identical maximum likelihoods. Consequences of population size estimation are illuminated, and the findings are illustrated at hand of two case studies. John Wiley and Sons Inc. 2022-08-15 2023-02 /pmc/articles/PMC10087693/ /pubmed/35971027 http://dx.doi.org/10.1002/bimj.202100343 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 Methods for Count Data
Böhning, Dankmar
On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods
title On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods
title_full On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods
title_fullStr On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods
title_full_unstemmed On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods
title_short On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods
title_sort on the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods
topic Methods for Count Data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10087693/
https://www.ncbi.nlm.nih.gov/pubmed/35971027
http://dx.doi.org/10.1002/bimj.202100343
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