Cargando…
Binomial-discrete Erlang-truncated exponential mixture and its application in cancer disease
Among diseases, cancer exhibits the fastest global spread, presenting a substantial challenge for patients, their families, and the communities they belong to. This paper is devoted to modeling such a disease as a special case. A newly proposed distribution called the binomial-discrete Erlang-trunca...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382481/ https://www.ncbi.nlm.nih.gov/pubmed/37507433 http://dx.doi.org/10.1038/s41598-023-38709-2 |
_version_ | 1785080679171620864 |
---|---|
author | El-Alosey, Alaa R. Eledum, Hussein |
author_facet | El-Alosey, Alaa R. Eledum, Hussein |
author_sort | El-Alosey, Alaa R. |
collection | PubMed |
description | Among diseases, cancer exhibits the fastest global spread, presenting a substantial challenge for patients, their families, and the communities they belong to. This paper is devoted to modeling such a disease as a special case. A newly proposed distribution called the binomial-discrete Erlang-truncated exponential (BDETE) is introduced. The BDETE is a mixture of binomial distribution with the number of trials (parameter [Formula: see text] ) taken after a discrete Erlang-truncated exponential distribution. A comprehensive mathematical treatment of the proposed distribution and expressions of its density, cumulative distribution function, survival function, failure rate function, Quantile function, moment generating function, Shannon entropy, order statistics, and stress-strength reliability, are provided. The distribution's parameters are estimated using the maximum likelihood method. Two real-world lifetime count data sets from the cancer disease, both of which are right-skewed and over-dispersed, are fitted using the proposed BDETE distribution to evaluate its efficacy and viability. We expect the findings to become standard works in probability theory and its related fields. |
format | Online Article Text |
id | pubmed-10382481 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103824812023-07-30 Binomial-discrete Erlang-truncated exponential mixture and its application in cancer disease El-Alosey, Alaa R. Eledum, Hussein Sci Rep Article Among diseases, cancer exhibits the fastest global spread, presenting a substantial challenge for patients, their families, and the communities they belong to. This paper is devoted to modeling such a disease as a special case. A newly proposed distribution called the binomial-discrete Erlang-truncated exponential (BDETE) is introduced. The BDETE is a mixture of binomial distribution with the number of trials (parameter [Formula: see text] ) taken after a discrete Erlang-truncated exponential distribution. A comprehensive mathematical treatment of the proposed distribution and expressions of its density, cumulative distribution function, survival function, failure rate function, Quantile function, moment generating function, Shannon entropy, order statistics, and stress-strength reliability, are provided. The distribution's parameters are estimated using the maximum likelihood method. Two real-world lifetime count data sets from the cancer disease, both of which are right-skewed and over-dispersed, are fitted using the proposed BDETE distribution to evaluate its efficacy and viability. We expect the findings to become standard works in probability theory and its related fields. Nature Publishing Group UK 2023-07-28 /pmc/articles/PMC10382481/ /pubmed/37507433 http://dx.doi.org/10.1038/s41598-023-38709-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article El-Alosey, Alaa R. Eledum, Hussein Binomial-discrete Erlang-truncated exponential mixture and its application in cancer disease |
title | Binomial-discrete Erlang-truncated exponential mixture and its application in cancer disease |
title_full | Binomial-discrete Erlang-truncated exponential mixture and its application in cancer disease |
title_fullStr | Binomial-discrete Erlang-truncated exponential mixture and its application in cancer disease |
title_full_unstemmed | Binomial-discrete Erlang-truncated exponential mixture and its application in cancer disease |
title_short | Binomial-discrete Erlang-truncated exponential mixture and its application in cancer disease |
title_sort | binomial-discrete erlang-truncated exponential mixture and its application in cancer disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382481/ https://www.ncbi.nlm.nih.gov/pubmed/37507433 http://dx.doi.org/10.1038/s41598-023-38709-2 |
work_keys_str_mv | AT elaloseyalaar binomialdiscreteerlangtruncatedexponentialmixtureanditsapplicationincancerdisease AT eledumhussein binomialdiscreteerlangtruncatedexponentialmixtureanditsapplicationincancerdisease |