The Extended Inverse Weibull Distribution: Properties and Applications
This paper proposes the new three-parameter type I half-logistic inverse Weibull (TIHLIW) distribution which generalizes the inverse Weibull model. The density function of the TIHLIW can be expressed as a linear combination of the inverse Weibull densities. Some mathematical quantities of the propos...
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Online Access: | http://dx.doi.org/10.1155/2020/3297693 |
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doaj-45f310b08451401b81f6aac8945ed8372020-11-25T04:01:59ZengHindawi-WileyComplexity1076-27871099-05262020-01-01202010.1155/2020/32976933297693The Extended Inverse Weibull Distribution: Properties and ApplicationsSaid Alkarni0Ahmed Z. Afify1I. Elbatal2M. Elgarhy3Department of Quantitative Analysis, King Saud University, Riyadh, Saudi ArabiaDepartment of Statistics, Mathematics and Insurance, BenhaUniversity, Banha, EgyptDepartment of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi ArabiaValley High Institute for Management Finance and Information Systems, Obour, Qaliubia, EgyptThis paper proposes the new three-parameter type I half-logistic inverse Weibull (TIHLIW) distribution which generalizes the inverse Weibull model. The density function of the TIHLIW can be expressed as a linear combination of the inverse Weibull densities. Some mathematical quantities of the proposed TIHLIW model are derived. Four estimation methods, namely, the maximum likelihood, least squares, weighted least squares, and Cramér–von Mises methods, are utilized to estimate the TIHLIW parameters. Simulation results are presented to assess the performance of the proposed estimation methods. The importance of the TIHLIW model is studied via a real data application.http://dx.doi.org/10.1155/2020/3297693 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Said Alkarni Ahmed Z. Afify I. Elbatal M. Elgarhy |
spellingShingle |
Said Alkarni Ahmed Z. Afify I. Elbatal M. Elgarhy The Extended Inverse Weibull Distribution: Properties and Applications Complexity |
author_facet |
Said Alkarni Ahmed Z. Afify I. Elbatal M. Elgarhy |
author_sort |
Said Alkarni |
title |
The Extended Inverse Weibull Distribution: Properties and Applications |
title_short |
The Extended Inverse Weibull Distribution: Properties and Applications |
title_full |
The Extended Inverse Weibull Distribution: Properties and Applications |
title_fullStr |
The Extended Inverse Weibull Distribution: Properties and Applications |
title_full_unstemmed |
The Extended Inverse Weibull Distribution: Properties and Applications |
title_sort |
extended inverse weibull distribution: properties and applications |
publisher |
Hindawi-Wiley |
series |
Complexity |
issn |
1076-2787 1099-0526 |
publishDate |
2020-01-01 |
description |
This paper proposes the new three-parameter type I half-logistic inverse Weibull (TIHLIW) distribution which generalizes the inverse Weibull model. The density function of the TIHLIW can be expressed as a linear combination of the inverse Weibull densities. Some mathematical quantities of the proposed TIHLIW model are derived. Four estimation methods, namely, the maximum likelihood, least squares, weighted least squares, and Cramér–von Mises methods, are utilized to estimate the TIHLIW parameters. Simulation results are presented to assess the performance of the proposed estimation methods. The importance of the TIHLIW model is studied via a real data application. |
url |
http://dx.doi.org/10.1155/2020/3297693 |
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