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Weighted power Maxwell distribution: Statistical inference and COVID-19 applications
During the course of this research, we came up with a brand new distribution that is superior; we then presented and analysed the mathematical properties of this distribution; finally, we assessed its fuzzy reliability function. Because the novel distribution provides a number of advantages, like th...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810183/ https://www.ncbi.nlm.nih.gov/pubmed/36595502 http://dx.doi.org/10.1371/journal.pone.0278659 |
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author | Almuqrin, Muqrin A. Almutlak, Salemah A. Gemeay, Ahmed M. Almetwally, Ehab M. Karakaya, Kadir Makumi, Nicholas Hussam, Eslam Aldallal, Ramy |
author_facet | Almuqrin, Muqrin A. Almutlak, Salemah A. Gemeay, Ahmed M. Almetwally, Ehab M. Karakaya, Kadir Makumi, Nicholas Hussam, Eslam Aldallal, Ramy |
author_sort | Almuqrin, Muqrin A. |
collection | PubMed |
description | During the course of this research, we came up with a brand new distribution that is superior; we then presented and analysed the mathematical properties of this distribution; finally, we assessed its fuzzy reliability function. Because the novel distribution provides a number of advantages, like the reality that its cumulative distribution function and probability density function both have a closed form, it is very useful in a wide range of disciplines that are related to data science. One of these fields is machine learning, which is a sub field of data science. We used both traditional methods and Bayesian methodologies in order to generate a large number of different estimates. A test setup might have been carried out to assess the effectiveness of both the classical and the Bayesian estimators. At last, three different sets of Covid-19 death analysis were done so that the effectiveness of the new model could be demonstrated. |
format | Online Article Text |
id | pubmed-9810183 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-98101832023-01-04 Weighted power Maxwell distribution: Statistical inference and COVID-19 applications Almuqrin, Muqrin A. Almutlak, Salemah A. Gemeay, Ahmed M. Almetwally, Ehab M. Karakaya, Kadir Makumi, Nicholas Hussam, Eslam Aldallal, Ramy PLoS One Research Article During the course of this research, we came up with a brand new distribution that is superior; we then presented and analysed the mathematical properties of this distribution; finally, we assessed its fuzzy reliability function. Because the novel distribution provides a number of advantages, like the reality that its cumulative distribution function and probability density function both have a closed form, it is very useful in a wide range of disciplines that are related to data science. One of these fields is machine learning, which is a sub field of data science. We used both traditional methods and Bayesian methodologies in order to generate a large number of different estimates. A test setup might have been carried out to assess the effectiveness of both the classical and the Bayesian estimators. At last, three different sets of Covid-19 death analysis were done so that the effectiveness of the new model could be demonstrated. Public Library of Science 2023-01-03 /pmc/articles/PMC9810183/ /pubmed/36595502 http://dx.doi.org/10.1371/journal.pone.0278659 Text en © 2023 Almuqrin 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 Almuqrin, Muqrin A. Almutlak, Salemah A. Gemeay, Ahmed M. Almetwally, Ehab M. Karakaya, Kadir Makumi, Nicholas Hussam, Eslam Aldallal, Ramy Weighted power Maxwell distribution: Statistical inference and COVID-19 applications |
title | Weighted power Maxwell distribution: Statistical inference and COVID-19 applications |
title_full | Weighted power Maxwell distribution: Statistical inference and COVID-19 applications |
title_fullStr | Weighted power Maxwell distribution: Statistical inference and COVID-19 applications |
title_full_unstemmed | Weighted power Maxwell distribution: Statistical inference and COVID-19 applications |
title_short | Weighted power Maxwell distribution: Statistical inference and COVID-19 applications |
title_sort | weighted power maxwell distribution: statistical inference and covid-19 applications |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810183/ https://www.ncbi.nlm.nih.gov/pubmed/36595502 http://dx.doi.org/10.1371/journal.pone.0278659 |
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