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On the Extended Generalized Inverted Kumaraswamy Distribution
In this work, we provide a new generated class of models, namely, the extended generalized inverted Kumaraswamy generated (EGIKw-G) family of distributions. Several structural properties (survival function (sf), hazard rate function (hrf), reverse hazard rate function (rhrf), quantile function (qf)...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8872654/ https://www.ncbi.nlm.nih.gov/pubmed/35222621 http://dx.doi.org/10.1155/2022/1612959 |
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author | Ramzan, Qasim Qamar, Sadia Amin, Muhammad Alshanbari, Huda M. Nazeer, Amna Elhassanein, Ahmed |
author_facet | Ramzan, Qasim Qamar, Sadia Amin, Muhammad Alshanbari, Huda M. Nazeer, Amna Elhassanein, Ahmed |
author_sort | Ramzan, Qasim |
collection | PubMed |
description | In this work, we provide a new generated class of models, namely, the extended generalized inverted Kumaraswamy generated (EGIKw-G) family of distributions. Several structural properties (survival function (sf), hazard rate function (hrf), reverse hazard rate function (rhrf), quantile function (qf) and median, s(th) raw moment, generating function, mean deviation (md), etc.) are provided. The estimates for parameters of new G class are derived via maximum likelihood estimation (MLE) method. The special models of the proposed class are discussed, and particular attention is given to one special model, the extended generalized inverted Kumaraswamy Burr XII (EGIKw-Burr XII) model. Estimators are evaluated via a Monte Carlo simulation (MCS). The superiority of EGIKw-Burr XII model is proved using a lifetime data applications. |
format | Online Article Text |
id | pubmed-8872654 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-88726542022-02-25 On the Extended Generalized Inverted Kumaraswamy Distribution Ramzan, Qasim Qamar, Sadia Amin, Muhammad Alshanbari, Huda M. Nazeer, Amna Elhassanein, Ahmed Comput Intell Neurosci Research Article In this work, we provide a new generated class of models, namely, the extended generalized inverted Kumaraswamy generated (EGIKw-G) family of distributions. Several structural properties (survival function (sf), hazard rate function (hrf), reverse hazard rate function (rhrf), quantile function (qf) and median, s(th) raw moment, generating function, mean deviation (md), etc.) are provided. The estimates for parameters of new G class are derived via maximum likelihood estimation (MLE) method. The special models of the proposed class are discussed, and particular attention is given to one special model, the extended generalized inverted Kumaraswamy Burr XII (EGIKw-Burr XII) model. Estimators are evaluated via a Monte Carlo simulation (MCS). The superiority of EGIKw-Burr XII model is proved using a lifetime data applications. Hindawi 2022-02-17 /pmc/articles/PMC8872654/ /pubmed/35222621 http://dx.doi.org/10.1155/2022/1612959 Text en Copyright © 2022 Qasim Ramzan et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ramzan, Qasim Qamar, Sadia Amin, Muhammad Alshanbari, Huda M. Nazeer, Amna Elhassanein, Ahmed On the Extended Generalized Inverted Kumaraswamy Distribution |
title | On the Extended Generalized Inverted Kumaraswamy Distribution |
title_full | On the Extended Generalized Inverted Kumaraswamy Distribution |
title_fullStr | On the Extended Generalized Inverted Kumaraswamy Distribution |
title_full_unstemmed | On the Extended Generalized Inverted Kumaraswamy Distribution |
title_short | On the Extended Generalized Inverted Kumaraswamy Distribution |
title_sort | on the extended generalized inverted kumaraswamy distribution |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8872654/ https://www.ncbi.nlm.nih.gov/pubmed/35222621 http://dx.doi.org/10.1155/2022/1612959 |
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