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A new extended gumbel distribution: Properties and application

A robust generalisation of the Gumbel distribution is proposed in this article. This family of distributions is based on the T-X paradigm. From a list of special distributions that have evolved as a result of this family, three separate models are also mentioned in this article. A linear combination...

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Autores principales: Fayomi, Aisha, Khan, Sadaf, Tahir, Muhammad Hussain, Algarni, Ali, Jamal, Farrukh, Abu-Shanab, Reman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140309/
https://www.ncbi.nlm.nih.gov/pubmed/35622822
http://dx.doi.org/10.1371/journal.pone.0267142
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author Fayomi, Aisha
Khan, Sadaf
Tahir, Muhammad Hussain
Algarni, Ali
Jamal, Farrukh
Abu-Shanab, Reman
author_facet Fayomi, Aisha
Khan, Sadaf
Tahir, Muhammad Hussain
Algarni, Ali
Jamal, Farrukh
Abu-Shanab, Reman
author_sort Fayomi, Aisha
collection PubMed
description A robust generalisation of the Gumbel distribution is proposed in this article. This family of distributions is based on the T-X paradigm. From a list of special distributions that have evolved as a result of this family, three separate models are also mentioned in this article. A linear combination of generalised exponential distributions can be used to characterise the density of a new family, which is critical in assessing some of the family’s properties. The statistical features of this family are determined, including exact formulations for the quantile function, ordinary and incomplete moments, generating function, and order statistics. The model parameters are estimated using the maximum likelihood method. Further, one of the unique models has been systematically studied. Along with conventional skewness measures, MacGillivray skewness is also used to quantify the skewness measure. The new probability distribution also enables us to determine certain critical risk indicators, both numerically and graphically. We use a simulated assessment of the suggested distribution, as well as apply three real-world data sets in modelling the proposed model, in order to ensure its authenticity and superiority.
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spelling pubmed-91403092022-05-28 A new extended gumbel distribution: Properties and application Fayomi, Aisha Khan, Sadaf Tahir, Muhammad Hussain Algarni, Ali Jamal, Farrukh Abu-Shanab, Reman PLoS One Research Article A robust generalisation of the Gumbel distribution is proposed in this article. This family of distributions is based on the T-X paradigm. From a list of special distributions that have evolved as a result of this family, three separate models are also mentioned in this article. A linear combination of generalised exponential distributions can be used to characterise the density of a new family, which is critical in assessing some of the family’s properties. The statistical features of this family are determined, including exact formulations for the quantile function, ordinary and incomplete moments, generating function, and order statistics. The model parameters are estimated using the maximum likelihood method. Further, one of the unique models has been systematically studied. Along with conventional skewness measures, MacGillivray skewness is also used to quantify the skewness measure. The new probability distribution also enables us to determine certain critical risk indicators, both numerically and graphically. We use a simulated assessment of the suggested distribution, as well as apply three real-world data sets in modelling the proposed model, in order to ensure its authenticity and superiority. Public Library of Science 2022-05-27 /pmc/articles/PMC9140309/ /pubmed/35622822 http://dx.doi.org/10.1371/journal.pone.0267142 Text en © 2022 Fayomi et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Fayomi, Aisha
Khan, Sadaf
Tahir, Muhammad Hussain
Algarni, Ali
Jamal, Farrukh
Abu-Shanab, Reman
A new extended gumbel distribution: Properties and application
title A new extended gumbel distribution: Properties and application
title_full A new extended gumbel distribution: Properties and application
title_fullStr A new extended gumbel distribution: Properties and application
title_full_unstemmed A new extended gumbel distribution: Properties and application
title_short A new extended gumbel distribution: Properties and application
title_sort new extended gumbel distribution: properties and application
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140309/
https://www.ncbi.nlm.nih.gov/pubmed/35622822
http://dx.doi.org/10.1371/journal.pone.0267142
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