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...
Autores principales: | , , , |
---|---|
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 |