Cargando…

Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia

The objective of this study is to construct a new distribution known as the weighted Burr–Hatke distribution (WBHD). The PDF and CDF of the WBHD are derived in a closed form. Moments, incomplete moments, and the quantile function of the proposed distribution are derived mathematically. Eleven estima...

Descripción completa

Detalles Bibliográficos
Autores principales: Aldallal, Ramy, Gemeay, Ahmed M., Hussam, Eslam, Kilai, Mutua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9616221/
https://www.ncbi.nlm.nih.gov/pubmed/36306316
http://dx.doi.org/10.1371/journal.pone.0276688
_version_ 1784820603258142720
author Aldallal, Ramy
Gemeay, Ahmed M.
Hussam, Eslam
Kilai, Mutua
author_facet Aldallal, Ramy
Gemeay, Ahmed M.
Hussam, Eslam
Kilai, Mutua
author_sort Aldallal, Ramy
collection PubMed
description The objective of this study is to construct a new distribution known as the weighted Burr–Hatke distribution (WBHD). The PDF and CDF of the WBHD are derived in a closed form. Moments, incomplete moments, and the quantile function of the proposed distribution are derived mathematically. Eleven estimate techniques for estimating the distribution parameters are discussed, and numerical simulations are utilised to evaluate the various approaches using partial and overall rankings. According to the findings of this study, it is recommended that the maximum product of spacing (MPSE) estimator of the WBHD is the best estimator according to overall rank table. The actuarial measurements were derived to the suggested distribution. By contrasting the WBHD with other competitive distributions using two different actual data sets collected from the COVID-19 mortality rates, we show the importance and flexibility of the WBHD.
format Online
Article
Text
id pubmed-9616221
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-96162212022-10-29 Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia Aldallal, Ramy Gemeay, Ahmed M. Hussam, Eslam Kilai, Mutua PLoS One Research Article The objective of this study is to construct a new distribution known as the weighted Burr–Hatke distribution (WBHD). The PDF and CDF of the WBHD are derived in a closed form. Moments, incomplete moments, and the quantile function of the proposed distribution are derived mathematically. Eleven estimate techniques for estimating the distribution parameters are discussed, and numerical simulations are utilised to evaluate the various approaches using partial and overall rankings. According to the findings of this study, it is recommended that the maximum product of spacing (MPSE) estimator of the WBHD is the best estimator according to overall rank table. The actuarial measurements were derived to the suggested distribution. By contrasting the WBHD with other competitive distributions using two different actual data sets collected from the COVID-19 mortality rates, we show the importance and flexibility of the WBHD. Public Library of Science 2022-10-28 /pmc/articles/PMC9616221/ /pubmed/36306316 http://dx.doi.org/10.1371/journal.pone.0276688 Text en © 2022 Aldallal 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
Aldallal, Ramy
Gemeay, Ahmed M.
Hussam, Eslam
Kilai, Mutua
Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia
title Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia
title_full Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia
title_fullStr Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia
title_full_unstemmed Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia
title_short Statistical modeling for COVID 19 infected patient’s data in Kingdom of Saudi Arabia
title_sort statistical modeling for covid 19 infected patient’s data in kingdom of saudi arabia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9616221/
https://www.ncbi.nlm.nih.gov/pubmed/36306316
http://dx.doi.org/10.1371/journal.pone.0276688
work_keys_str_mv AT aldallalramy statisticalmodelingforcovid19infectedpatientsdatainkingdomofsaudiarabia
AT gemeayahmedm statisticalmodelingforcovid19infectedpatientsdatainkingdomofsaudiarabia
AT hussameslam statisticalmodelingforcovid19infectedpatientsdatainkingdomofsaudiarabia
AT kilaimutua statisticalmodelingforcovid19infectedpatientsdatainkingdomofsaudiarabia