Cargando…
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...
Autor principal: | |
---|---|
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 |
_version_ | 1785022407625408512 |
---|---|
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. |
format | Online Article Text |
id | pubmed-10087693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT bohningdankmar ontheequivalenceofoneinflatedzerotruncatedandzerotruncatedoneinflatedcountdatalikelihoods |