Modeling to medical and economic data using: The transmuted power unit inverse Lindley distribution
Modeling biomedical and economic data accurately poses considerable challenges due to the complexity of these datasets, which frequently display variability, skewness, and heavy tails. Standard probability distributions often do not adequately represent these complexities, resulting in erroneous con...
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| Language: | English |
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Elsevier
2025-02-01
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| Series: | Alexandria Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016824014261 |
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| author | Eman A. Eldessouky Osama H. Mahmoud Hassan Badr Aloraini Ibrahim Elbatal |
| author_facet | Eman A. Eldessouky Osama H. Mahmoud Hassan Badr Aloraini Ibrahim Elbatal |
| author_sort | Eman A. Eldessouky |
| collection | DOAJ |
| description | Modeling biomedical and economic data accurately poses considerable challenges due to the complexity of these datasets, which frequently display variability, skewness, and heavy tails. Standard probability distributions often do not adequately represent these complexities, resulting in erroneous conclusions. This study introduces the transmuted power unit inverse Lindley distribution (TPUILD) distribution as a novel extension of the power unit inverse Lindley distribution (PUILD), developed using a transmuted transformation technique to address existing challenges. The density plots of the TPUILD highlight its significant potential for practical applications. The hazard rate function may display both increasing and decreasing patterns, offering significant flexibility in the formulation of statistical models for biomedical and economic research. Several significant properties of the TPUILD, encompassing various reliability measures, moments, incomplete moments, and order statistics are computed. The parameters of the TPUILD were estimated through the maximum likelihood method of estimation, accompanied by a simulation study to evaluate the performance of these parameters. The proposed distribution was applied to two real datasets from biomedical and economic sciences to illustrate its practical utility. The goodness-of-fit was assessed through multiple measures, revealing that the TPUILD offers a markedly superior fit in comparison to the inverse Topp-Leone, power XLindley, truncated power Lomax, truncated Weibull, exponential Pareto, Kumaraswamy Kumaraswamy, exponentiated Kumaraswamy, and Marshall–Olkin Kumaraswamy models. distributions. Due to its enhanced fit relative to established models, the TPUILD is recommended for data modeling in economic and biomedical domains. |
| format | Article |
| id | doaj-art-58a426b9d14241bcb0369791189e7ce4 |
| institution | Kabale University |
| issn | 1110-0168 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj-art-58a426b9d14241bcb0369791189e7ce42025-02-07T04:47:00ZengElsevierAlexandria Engineering Journal1110-01682025-02-01113633647Modeling to medical and economic data using: The transmuted power unit inverse Lindley distributionEman A. Eldessouky0Osama H. Mahmoud Hassan1Badr Aloraini2Ibrahim Elbatal3Department of Quantitative Methods, Applied College, King Faisal University, Al-Ahsa 31982, Saudi Arabia; Corresponding author.Department of Quantitative Methods, School of Business, King Faisal University, Al-Ahsa 31982, Saudi ArabiaDepartment of Mathematics, College of Science and Humanities, Shaqra University, 11691 Shaqra, Saudi ArabiaDepartment of Mathematics and Statistics, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi ArabiaModeling biomedical and economic data accurately poses considerable challenges due to the complexity of these datasets, which frequently display variability, skewness, and heavy tails. Standard probability distributions often do not adequately represent these complexities, resulting in erroneous conclusions. This study introduces the transmuted power unit inverse Lindley distribution (TPUILD) distribution as a novel extension of the power unit inverse Lindley distribution (PUILD), developed using a transmuted transformation technique to address existing challenges. The density plots of the TPUILD highlight its significant potential for practical applications. The hazard rate function may display both increasing and decreasing patterns, offering significant flexibility in the formulation of statistical models for biomedical and economic research. Several significant properties of the TPUILD, encompassing various reliability measures, moments, incomplete moments, and order statistics are computed. The parameters of the TPUILD were estimated through the maximum likelihood method of estimation, accompanied by a simulation study to evaluate the performance of these parameters. The proposed distribution was applied to two real datasets from biomedical and economic sciences to illustrate its practical utility. The goodness-of-fit was assessed through multiple measures, revealing that the TPUILD offers a markedly superior fit in comparison to the inverse Topp-Leone, power XLindley, truncated power Lomax, truncated Weibull, exponential Pareto, Kumaraswamy Kumaraswamy, exponentiated Kumaraswamy, and Marshall–Olkin Kumaraswamy models. distributions. Due to its enhanced fit relative to established models, the TPUILD is recommended for data modeling in economic and biomedical domains.http://www.sciencedirect.com/science/article/pii/S1110016824014261Transmuted generated familyPower unit inverse Lindley distributionReliabilityMomentsOrder statisticsSimulation |
| spellingShingle | Eman A. Eldessouky Osama H. Mahmoud Hassan Badr Aloraini Ibrahim Elbatal Modeling to medical and economic data using: The transmuted power unit inverse Lindley distribution Alexandria Engineering Journal Transmuted generated family Power unit inverse Lindley distribution Reliability Moments Order statistics Simulation |
| title | Modeling to medical and economic data using: The transmuted power unit inverse Lindley distribution |
| title_full | Modeling to medical and economic data using: The transmuted power unit inverse Lindley distribution |
| title_fullStr | Modeling to medical and economic data using: The transmuted power unit inverse Lindley distribution |
| title_full_unstemmed | Modeling to medical and economic data using: The transmuted power unit inverse Lindley distribution |
| title_short | Modeling to medical and economic data using: The transmuted power unit inverse Lindley distribution |
| title_sort | modeling to medical and economic data using the transmuted power unit inverse lindley distribution |
| topic | Transmuted generated family Power unit inverse Lindley distribution Reliability Moments Order statistics Simulation |
| url | http://www.sciencedirect.com/science/article/pii/S1110016824014261 |
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