New bounded probability model: Properties, estimation, and applications
The article introduces a new unit distribution, an extension of Tiessier distribution, characterized by a versatile hazard function capable of adopting diverse shapes such as bathtub or N-shaped curves. An exploration of the fundamental properties of this distribution is undertaken, accompanied by t...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Heliyon |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024149961 |
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| author | Ahmed M. Gemeay Laxmi Prasad Sapkota Yusra A. Tashkandy M.E. Bakr Oluwafemi Samson Balogun Eslam Hussam |
| author_facet | Ahmed M. Gemeay Laxmi Prasad Sapkota Yusra A. Tashkandy M.E. Bakr Oluwafemi Samson Balogun Eslam Hussam |
| author_sort | Ahmed M. Gemeay |
| collection | DOAJ |
| description | The article introduces a new unit distribution, an extension of Tiessier distribution, characterized by a versatile hazard function capable of adopting diverse shapes such as bathtub or N-shaped curves. An exploration of the fundamental properties of this distribution is undertaken, accompanied by the implementation of the maximum likelihood estimation technique and eleven alternative methods to approximate its parameters effectively. Through a simulation study, the article effectively demonstrates the precision of these parameter estimation methods, even when dealing with small sample sizes. Two datasets are employed to apply the novel distribution, subjecting it to a comprehensive evaluation against established models utilizing a range of model selection criteria and goodness of fit tests. Notably, the article illustrates that the performance of the new distribution surpasses that of existing models in effectively capturing data patterns. Beyond its empirical contributions, the article highlights the potential cross-disciplinary applications of the new distribution in many fields while concurrently advancing the realms of probability theory and statistical inferences. |
| format | Article |
| id | doaj-art-ba92f63047ed4922a60abca1f4e8a277 |
| institution | OA Journals |
| issn | 2405-8440 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-ba92f63047ed4922a60abca1f4e8a2772025-08-20T01:59:30ZengElsevierHeliyon2405-84402024-12-011023e3896510.1016/j.heliyon.2024.e38965New bounded probability model: Properties, estimation, and applicationsAhmed M. Gemeay0Laxmi Prasad Sapkota1Yusra A. Tashkandy2M.E. Bakr3Oluwafemi Samson Balogun4Eslam Hussam5Department of Mathematics, Faculty of Science, Tanta University, Tanta 31527, EgyptDepartment of Statistics, Tribhuvan University, Tribhuvan Multiple Campus, Palpa, NepalDepartment of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi ArabiaDepartment of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi ArabiaDepartment of Computing, University of Eastern Finland, FI-70211, Kuopio, FinlandDepartment of Mathematics, Faculty of Science, Helwan University, Cairo, EgyptThe article introduces a new unit distribution, an extension of Tiessier distribution, characterized by a versatile hazard function capable of adopting diverse shapes such as bathtub or N-shaped curves. An exploration of the fundamental properties of this distribution is undertaken, accompanied by the implementation of the maximum likelihood estimation technique and eleven alternative methods to approximate its parameters effectively. Through a simulation study, the article effectively demonstrates the precision of these parameter estimation methods, even when dealing with small sample sizes. Two datasets are employed to apply the novel distribution, subjecting it to a comprehensive evaluation against established models utilizing a range of model selection criteria and goodness of fit tests. Notably, the article illustrates that the performance of the new distribution surpasses that of existing models in effectively capturing data patterns. Beyond its empirical contributions, the article highlights the potential cross-disciplinary applications of the new distribution in many fields while concurrently advancing the realms of probability theory and statistical inferences.http://www.sciencedirect.com/science/article/pii/S2405844024149961 |
| spellingShingle | Ahmed M. Gemeay Laxmi Prasad Sapkota Yusra A. Tashkandy M.E. Bakr Oluwafemi Samson Balogun Eslam Hussam New bounded probability model: Properties, estimation, and applications Heliyon |
| title | New bounded probability model: Properties, estimation, and applications |
| title_full | New bounded probability model: Properties, estimation, and applications |
| title_fullStr | New bounded probability model: Properties, estimation, and applications |
| title_full_unstemmed | New bounded probability model: Properties, estimation, and applications |
| title_short | New bounded probability model: Properties, estimation, and applications |
| title_sort | new bounded probability model properties estimation and applications |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024149961 |
| work_keys_str_mv | AT ahmedmgemeay newboundedprobabilitymodelpropertiesestimationandapplications AT laxmiprasadsapkota newboundedprobabilitymodelpropertiesestimationandapplications AT yusraatashkandy newboundedprobabilitymodelpropertiesestimationandapplications AT mebakr newboundedprobabilitymodelpropertiesestimationandapplications AT oluwafemisamsonbalogun newboundedprobabilitymodelpropertiesestimationandapplications AT eslamhussam newboundedprobabilitymodelpropertiesestimationandapplications |