A Gull Alpha Power Weibull distribution with applications to real and simulated data

In this paper, we produced a new family of distribution called Gull Alpha Power Family of distributions (GAPF). A Special case of GAPF is derived by considering the Weibull distribution as a baseline distribution called Gull Alpha Power Weibull distribution (GAPW). The suitability of the proposed di...

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Detalles Bibliográficos
Autores principales: Ijaz, Muhammad, Asim, Syed Muhammad, Alamgir, Farooq, Muhammad, Khan, Sajjad Ahmad, Manzoor, Sadaf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7292407/
https://www.ncbi.nlm.nih.gov/pubmed/32530965
http://dx.doi.org/10.1371/journal.pone.0233080
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author Ijaz, Muhammad
Asim, Syed Muhammad
Alamgir,
Farooq, Muhammad
Khan, Sajjad Ahmad
Manzoor, Sadaf
author_facet Ijaz, Muhammad
Asim, Syed Muhammad
Alamgir,
Farooq, Muhammad
Khan, Sajjad Ahmad
Manzoor, Sadaf
author_sort Ijaz, Muhammad
collection PubMed
description In this paper, we produced a new family of distribution called Gull Alpha Power Family of distributions (GAPF). A Special case of GAPF is derived by considering the Weibull distribution as a baseline distribution called Gull Alpha Power Weibull distribution (GAPW). The suitability of the proposed distribution derives from its ability to model both the monotonic and non-monotonic hazard rate functions which are a common practice in survival analysis and reliability engineering. Various statistical properties were derived in addition to their special cases. The unknown parameters of the model are estimated using the maximum likelihood method. Moreover, the usefulness of the proposed distribution is supported by using two real lifetime data sets as well as simulated data.
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spelling pubmed-72924072020-06-18 A Gull Alpha Power Weibull distribution with applications to real and simulated data Ijaz, Muhammad Asim, Syed Muhammad Alamgir, Farooq, Muhammad Khan, Sajjad Ahmad Manzoor, Sadaf PLoS One Research Article In this paper, we produced a new family of distribution called Gull Alpha Power Family of distributions (GAPF). A Special case of GAPF is derived by considering the Weibull distribution as a baseline distribution called Gull Alpha Power Weibull distribution (GAPW). The suitability of the proposed distribution derives from its ability to model both the monotonic and non-monotonic hazard rate functions which are a common practice in survival analysis and reliability engineering. Various statistical properties were derived in addition to their special cases. The unknown parameters of the model are estimated using the maximum likelihood method. Moreover, the usefulness of the proposed distribution is supported by using two real lifetime data sets as well as simulated data. Public Library of Science 2020-06-12 /pmc/articles/PMC7292407/ /pubmed/32530965 http://dx.doi.org/10.1371/journal.pone.0233080 Text en © 2020 Ijaz et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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
Ijaz, Muhammad
Asim, Syed Muhammad
Alamgir,
Farooq, Muhammad
Khan, Sajjad Ahmad
Manzoor, Sadaf
A Gull Alpha Power Weibull distribution with applications to real and simulated data
title A Gull Alpha Power Weibull distribution with applications to real and simulated data
title_full A Gull Alpha Power Weibull distribution with applications to real and simulated data
title_fullStr A Gull Alpha Power Weibull distribution with applications to real and simulated data
title_full_unstemmed A Gull Alpha Power Weibull distribution with applications to real and simulated data
title_short A Gull Alpha Power Weibull distribution with applications to real and simulated data
title_sort gull alpha power weibull distribution with applications to real and simulated data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7292407/
https://www.ncbi.nlm.nih.gov/pubmed/32530965
http://dx.doi.org/10.1371/journal.pone.0233080
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