A novel Compound-Pareto model with applications and reliability peaks above a random threshold value at risk analysis
Abstract This paper aims to model the bimodal and right-skewed aircraft windshield data using a novel compounded-Pareto distribution. The method of maximum likelihood is employed to estimate the unknown model parameters, and the performance of the estimators under finite samples is evaluated through...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-07426-3 |
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| author | Mohammad Abiad M. M. Abd El-Raouf Haitham M. Yousof M. E. Bakr Oluwafemi Samson Balogun M. Yusuf Getachew Tekle Mekiso Yusra A. Tashkandy |
| author_facet | Mohammad Abiad M. M. Abd El-Raouf Haitham M. Yousof M. E. Bakr Oluwafemi Samson Balogun M. Yusuf Getachew Tekle Mekiso Yusra A. Tashkandy |
| author_sort | Mohammad Abiad |
| collection | DOAJ |
| description | Abstract This paper aims to model the bimodal and right-skewed aircraft windshield data using a novel compounded-Pareto distribution. The method of maximum likelihood is employed to estimate the unknown model parameters, and the performance of the estimators under finite samples is evaluated through a comprehensive simulation study. The practical applicability of the proposed model is demonstrated using two real-world reliability datasets. Reliability analysis based on Peaks Over a Random Threshold Value at Risk (PORT-VAR) is crucial for aircraft windshield manufacturers, as it provides a rigorous assessment of extreme failure events and service times-key factors in ensuring product safety and longevity. By identifying the frequency and severity of failures exceeding specific VAR thresholds, this analysis enables companies to understand the upper bounds of their products’ performance under stress, optimize designs for enhanced durability, and develop proactive maintenance strategies. In this paper, we present a comprehensive reliability PORT-VAR analysis to support these objectives and highlight the relevance of the proposed model in extreme value risk modeling and real-world reliability scenarios. |
| format | Article |
| id | doaj-art-9081cac045324aa1b1fd4b24df39fd9c |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-9081cac045324aa1b1fd4b24df39fd9c2025-08-20T03:45:26ZengNature PortfolioScientific Reports2045-23222025-07-0115112210.1038/s41598-025-07426-3A novel Compound-Pareto model with applications and reliability peaks above a random threshold value at risk analysisMohammad Abiad0M. M. Abd El-Raouf1Haitham M. Yousof2M. E. Bakr3Oluwafemi Samson Balogun4M. Yusuf5Getachew Tekle Mekiso6Yusra A. Tashkandy7College of Business Administration, American University of the Middle EastBasic and Applied Science Institute, Arab Academy for Science, Technology and Maritime Transport (AASTMT)Department of Statistics, Mathematics and Insurance, Benha UniversityDepartment of Statistics and Operations Research, College of Science, King Saud UniversityDepartment of Computing, Faculty of Science, Forestry and Technology, University of Eastern FinlandDepartment of Mathematics, Faculty of Science, Helwan universityDepartment of Statistics, Wachemo UniversityDepartment of Statistics and Operations Research, College of Science, King Saud UniversityAbstract This paper aims to model the bimodal and right-skewed aircraft windshield data using a novel compounded-Pareto distribution. The method of maximum likelihood is employed to estimate the unknown model parameters, and the performance of the estimators under finite samples is evaluated through a comprehensive simulation study. The practical applicability of the proposed model is demonstrated using two real-world reliability datasets. Reliability analysis based on Peaks Over a Random Threshold Value at Risk (PORT-VAR) is crucial for aircraft windshield manufacturers, as it provides a rigorous assessment of extreme failure events and service times-key factors in ensuring product safety and longevity. By identifying the frequency and severity of failures exceeding specific VAR thresholds, this analysis enables companies to understand the upper bounds of their products’ performance under stress, optimize designs for enhanced durability, and develop proactive maintenance strategies. In this paper, we present a comprehensive reliability PORT-VAR analysis to support these objectives and highlight the relevance of the proposed model in extreme value risk modeling and real-world reliability scenarios.https://doi.org/10.1038/s41598-025-07426-3PORT-VARRandom ThresholdPhysical DataAircraft WindshieldPareto ModelsReliability Modeling |
| spellingShingle | Mohammad Abiad M. M. Abd El-Raouf Haitham M. Yousof M. E. Bakr Oluwafemi Samson Balogun M. Yusuf Getachew Tekle Mekiso Yusra A. Tashkandy A novel Compound-Pareto model with applications and reliability peaks above a random threshold value at risk analysis Scientific Reports PORT-VAR Random Threshold Physical Data Aircraft Windshield Pareto Models Reliability Modeling |
| title | A novel Compound-Pareto model with applications and reliability peaks above a random threshold value at risk analysis |
| title_full | A novel Compound-Pareto model with applications and reliability peaks above a random threshold value at risk analysis |
| title_fullStr | A novel Compound-Pareto model with applications and reliability peaks above a random threshold value at risk analysis |
| title_full_unstemmed | A novel Compound-Pareto model with applications and reliability peaks above a random threshold value at risk analysis |
| title_short | A novel Compound-Pareto model with applications and reliability peaks above a random threshold value at risk analysis |
| title_sort | novel compound pareto model with applications and reliability peaks above a random threshold value at risk analysis |
| topic | PORT-VAR Random Threshold Physical Data Aircraft Windshield Pareto Models Reliability Modeling |
| url | https://doi.org/10.1038/s41598-025-07426-3 |
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