The Survival Power Weibull Distribution With Application
Keywords:
Weibull distribution; Maximum likelihood estimation; Entropy; Monte Carlo simulation; Family of distributions.
Abstract
الهدف الأساسي من هذا البحث هو التحقيق في توزيع عمر جديد يتميز بثلاثة معلمات، والتي تم إنشاؤها من خلال دمج توزيع Weibull وعائلة Survival Powe-G. يشار إلى النموذج الذي تم تقديمه مؤخرًا باسم توزيع SPW. يتمتع التوزيع الذي تم صياغته حديثًا بميزة النمذجة الفعالة لأنواع مختلفة من البيانات، وبالتالي يثبت أنه مفيد في مجالات إحصاءات الموثوقية وعمر الحياة. يتم فحص العديد من الخصائص الإحصائية ذات الصلة بتوزيع SPW في هذه الدراسة. نهج التقدير الموصى به هو طريقة الاحتمالية القصوى. يتم تقديم الاختبارات التجريبية لتوزيع SPW باستخدام مجموعتين من البيانات الحقيقية. علاوة على ذلك، يوضح توزيع SPW ملاءمة جيدة، مدعومة بمقارنات مع نماذج تعتمد على Weibull وتوزيعات بديلة أخرى باستخدام العديد من تقييمات جودة الملاءمة.References
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2. B. Roger, P. Chamila, S James and T. Alexandre, The linearly decreasing stress Weibull (LDSWeibull): a new Weibull-like
distribution, Journal of Statistical Distributions and Applications, vol. 6, no. 1, pp. 1-–21, 2019.
3. A. Teamah, A. Elbanna and A. Gemeay, Right Truncated Fr´echet-Weibull Distribution: Statistical Properties and Application, Delta
Journal of Science, vol. 41, no. 1, pp. 20-–29, 2019.
4. M. Almazah, Finding a compound weibull distribution, International Journal of Statistics and Applied Mathematics, vol. 5, no. 2,
pp. 111-–116, 2020.
5. L. Benkhelifa, The Weibull Birnbaum-Saunders distribution and its applications, Statistics, Optimization & Information Computing,
vol. 9, no. 1, pp. 61-–81, 2021.
6. X. Jia, S. Nadarajah and B. Guo, Inference on q-Weibull parameters, Stat Papers, vol. 61, no. 2, pp. 575-–593, 2020.
7. E. Nwezza, C. Ogbuehi, U. Uwadi and C. Omekara, The Gumbel Marshall-Olkin-Weibull distribution: Properties and applications,
International journal of scientific and research publications, vol. 10, no. 8, pp. 406-–418, 2020.
8. M. Hamed, The mixture weibull-generalized gamma distribution, Advances and applications in statistics, vol. 62, no. 2, pp. 139-
–171, 2020.
9. A. Ishaq and A. Abiodun, The Maxwell Weibull Distribution in Modeling Lifetime Datasets, Annals of Data Science, vol. 7, no. 4,
pp. 639-–662, 2020.
10. N. Hassan, H. Kalt, H. Aal-Rkhais and A. Hashoosh, The Weibull Lindley: General family of probability distributions, Mathematics
in Engineering, Science and Aerospace, vol. 12, no. 1, pp. 29–42, 2021.
11. B. Oluyede, F. Mutiso and S. Huang, The Log Generalized Lindley-Weibull Distribution with Application, Journal of data science,
vol. 13, no. 2, pp. 281-–310, 2021.
12. M. Alizadeh, M. Khan, M. Rasekhi and G. Hamedani, A new generalized modified Weibull distribution, Statistics, Optimization &
Information Computing, vol. 9, no. 1, pp. 17-–34, 2021.
13. W. Emam and Y. Tashkandy, Khalil New Generalized Weibull Distribution Based on Ranked Samples: Estimation, Mathematical
Properties, and Application to COVID-19 Data, Symmetry, vol. 14, no. 5, pp. 853, 2022.
14. E. Nwezza, U. Uwadi and C. Okonkwo, A new generalized transmuted weibull distribution: properties and applications,
International journal of advanced statistics and probability, vol. 9, no. 1, pp. 22-–29, 2022.
15. H. Adnan, N. Hassan and H. Jassim, The Weibull Lindley Rayleigh distribution, AIP Conference Proceedings, vol. 2414, no. 1, p.
040064, 2023.
16. M. Mukhlif and H. Saieed, Study of Alpha Power Weibull Distribution with Application, Iraqi Journal of Statistical Sciences, vol.
21, no. 1, pp. 112-–126, 2024.
17. I. Anabike, J. Okoli, P. Chukwuma, C. Igbokwe, D. Ekemezie and P. Ibeakuziei, A New Weibull-Exponential Distribution with
Properties and Applications, Asian Journal of Mathematics and Computer Research, vol. 31, no. 3, pp. 40-–52, 2024.
18. H. Kalt, A New Family of Continuous Distributions with Applications, Statistics, Optimization & Information Computing, vol. 12,
no. 6, pp. 1710-–1724, 2024.
19. J. Kenney and E. Keeping, Linear regression and correlation, Mathematics of statistics, vol. 1, pp. 252-–285, 1962.
20. J. Moors, A quantile alternative for kurtosis, Journal of the Royal Statistical Society: Series D (The Statistician), vol. 37, no. 1, pp.
25-–32, 1988.
21. T. Bjerkedal, Acquisition of Resistance in Guinea Pies infected with Different Doses of Virulent Tubercle Bacilli, American Journal
of Hygiene, vol. 72, no. 1, 1960.
22. H. Kalt and I. Hussein, Bayesian Estimation for Parameters and the Survival Function of Modifed Weibull Distribution using Tierney
and Kadane’s Approximation, Jour of Adv Research in Dynamical & Control Systems, vol. 10, no. 10 Special Issue, pp. 1960-–1970,
2018.
23. T. Alharbi and F. Hamad, An Optimal Strategy for Estimating Weibull distribution Parameters by Using Maximum Likelihood
Method, Statistics, Optimization & Information Computing, vol. 12, no. 5, pp. 1342-–1351, 2024.
24. H. Kalt, and M. Abd Al-Rahem, Comparison of four methods to estimate the scale parameter for Extended Poisson Exponential
distribution, IOP Conference Series: Materials Science and Engineering, vol. 571, no. 1, 2019.
25. E. Lee, Statistical methods for survival data analysis, John Wiley & Sons, 2003.
26. B. Al-Zahrani and H. Sagor, Statistical analysis of the Lomax–Logarithmic distribution, Journal of Statistical Computation and
Simulation, vol. 85, no. 9, pp. 1883-–1901, 2015.
27. H. Kalt and I. Hussein, A comparison of MLE method and OLS for the estimation of modified Weibull distribution parameters by
using the simulation., ARPN Journal of Engineering and Applied Sciences, vol. 13, no. 17, pp. 4833-–4839, 2018.
28. D. Murthy, M. Xie and R. Jiang, Weibull models., John Wiley and Sons, New Jersey, 2004.
Published
2025-02-24
How to Cite
Kalt, H., & Abdul Sada, M. T. (2025). The Survival Power Weibull Distribution With Application. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-2318
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Research Articles
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