Model Checking with Right Censored Data Using Relative Belief Ratio

Model checking is a topic of special interest in statistics. When data are censored, the problem becomes more difficult. This paper employs the relative belief ratio and the beta-Stacy process to develop a method for model checking in the presence of right-censored data. The proposed method for the...

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Detalles Bibliográficos
Autores principales: Al-Labadi, Luai, Alzaatreh, Ayman, Asuncion, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689107/
https://www.ncbi.nlm.nih.gov/pubmed/36359670
http://dx.doi.org/10.3390/e24111579
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author Al-Labadi, Luai
Alzaatreh, Ayman
Asuncion, Mark
author_facet Al-Labadi, Luai
Alzaatreh, Ayman
Asuncion, Mark
author_sort Al-Labadi, Luai
collection PubMed
description Model checking is a topic of special interest in statistics. When data are censored, the problem becomes more difficult. This paper employs the relative belief ratio and the beta-Stacy process to develop a method for model checking in the presence of right-censored data. The proposed method for the given model of interest compares the concentration of the posterior distribution to the concentration of the prior distribution using a relative belief ratio. We propose a computational algorithm for the method and then illustrate the method through several data analysis examples.
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spelling pubmed-96891072022-11-25 Model Checking with Right Censored Data Using Relative Belief Ratio Al-Labadi, Luai Alzaatreh, Ayman Asuncion, Mark Entropy (Basel) Article Model checking is a topic of special interest in statistics. When data are censored, the problem becomes more difficult. This paper employs the relative belief ratio and the beta-Stacy process to develop a method for model checking in the presence of right-censored data. The proposed method for the given model of interest compares the concentration of the posterior distribution to the concentration of the prior distribution using a relative belief ratio. We propose a computational algorithm for the method and then illustrate the method through several data analysis examples. MDPI 2022-10-31 /pmc/articles/PMC9689107/ /pubmed/36359670 http://dx.doi.org/10.3390/e24111579 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Al-Labadi, Luai
Alzaatreh, Ayman
Asuncion, Mark
Model Checking with Right Censored Data Using Relative Belief Ratio
title Model Checking with Right Censored Data Using Relative Belief Ratio
title_full Model Checking with Right Censored Data Using Relative Belief Ratio
title_fullStr Model Checking with Right Censored Data Using Relative Belief Ratio
title_full_unstemmed Model Checking with Right Censored Data Using Relative Belief Ratio
title_short Model Checking with Right Censored Data Using Relative Belief Ratio
title_sort model checking with right censored data using relative belief ratio
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689107/
https://www.ncbi.nlm.nih.gov/pubmed/36359670
http://dx.doi.org/10.3390/e24111579
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