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The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data

This paper aims at defining an optimal statistical model for the COVID-19 distribution in the United Kingdom, and Canada. A combining the inverted Topp–Leone distribution and the odd Weibull family introduces a new lifetime distribution with a three-parameter to formulate the odd Weibull inverted To...

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Autor principal: Almetwally, Ehab M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041244/
http://dx.doi.org/10.1007/s40745-021-00329-w
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author Almetwally, Ehab M.
author_facet Almetwally, Ehab M.
author_sort Almetwally, Ehab M.
collection PubMed
description This paper aims at defining an optimal statistical model for the COVID-19 distribution in the United Kingdom, and Canada. A combining the inverted Topp–Leone distribution and the odd Weibull family introduces a new lifetime distribution with a three-parameter to formulate the odd Weibull inverted Topp–Leone (OWITL) distribution. As a simple linear representation, hazard rate function, and moment function, this new distribution has several nice properties. To estimate the unknown parameters of OWITL distribution, maximum likelihood, least-square, weighted least-squares, maximum product spacing, Cramér–von Mises estimators, and Anderson–Darling estimation methods are used. To evaluate the use of estimation techniques, a numerical outcome of the Monte Carlo simulation is obtained.
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spelling pubmed-80412442021-04-13 The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data Almetwally, Ehab M. Ann. Data. Sci. Article This paper aims at defining an optimal statistical model for the COVID-19 distribution in the United Kingdom, and Canada. A combining the inverted Topp–Leone distribution and the odd Weibull family introduces a new lifetime distribution with a three-parameter to formulate the odd Weibull inverted Topp–Leone (OWITL) distribution. As a simple linear representation, hazard rate function, and moment function, this new distribution has several nice properties. To estimate the unknown parameters of OWITL distribution, maximum likelihood, least-square, weighted least-squares, maximum product spacing, Cramér–von Mises estimators, and Anderson–Darling estimation methods are used. To evaluate the use of estimation techniques, a numerical outcome of the Monte Carlo simulation is obtained. Springer Berlin Heidelberg 2021-04-12 2022 /pmc/articles/PMC8041244/ http://dx.doi.org/10.1007/s40745-021-00329-w Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Almetwally, Ehab M.
The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data
title The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data
title_full The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data
title_fullStr The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data
title_full_unstemmed The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data
title_short The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data
title_sort odd weibull inverse topp–leone distribution with applications to covid-19 data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041244/
http://dx.doi.org/10.1007/s40745-021-00329-w
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