New bounded probability model: Properties, estimation, and applications.
| Autor: | Gemeay AM; Department of Mathematics, Faculty of Science, Tanta University, Tanta 31527, Egypt., Sapkota LP; Department of Statistics, Tribhuvan University, Tribhuvan Multiple Campus, Palpa, Nepal., Tashkandy YA; Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia., Bakr ME; Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia., Balogun OS; Department of Computing, University of Eastern Finland, FI-70211, Kuopio, Finland., Hussam E; Department of Mathematics, Faculty of Science, Helwan University, Cairo, Egypt. |
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| Jazyk: | angličtina |
| Zdroj: | Heliyon [Heliyon] 2024 Oct 09; Vol. 10 (23), pp. e38965. Date of Electronic Publication: 2024 Oct 09 (Print Publication: 2024). |
| DOI: | 10.1016/j.heliyon.2024.e38965 |
| Abstrakt: | 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. Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (© 2024 Published by Elsevier Ltd.) |
| Databáze: | MEDLINE |
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