Modified generalized Weibull distribution: theory and applications

被引:13
|
作者
Shama, Mustafa S. [1 ,2 ]
Alharthi, Amirah Saeed [3 ]
Almulhim, Fatimah A. [4 ]
Gemeay, Ahmed M. [5 ]
Meraou, Mohammed Amine [6 ]
Mustafa, Manahil SidAhmed [7 ]
Hussam, Eslam [8 ]
Aljohani, Hassan M. [3 ]
机构
[1] King Saud Univ, Dept Basic Sci, CFY, Riyadh 12373, Saudi Arabia
[2] Osim Higher Inst Adm Sci, Dept Math & Stat, Osim 12961, Egypt
[3] Taif Univ, Coll Sci, Dept Math & Stat, POB 11099, Taif 21944, Saudi Arabia
[4] Princess Nourah bint Abdulrahman Univ, Coll Sci, Dept Math Sci, POB 84428, Riyadh 11671, Saudi Arabia
[5] Tanta Univ, Fac Sci, Dept Math, Tanta 31527, Egypt
[6] Univ Djillali Liabes Sidi Bel Abbes, Lab Stat & Stochast Proc, BP 89, Sidi Bel Abbes 22000, Algeria
[7] Univ Tabuk, Fac Sci, Dept Stat, Tabuk, Saudi Arabia
[8] Helwan Univ, Fac Sci, Dept Math, Cairo, Egypt
关键词
EXTENSION;
D O I
10.1038/s41598-023-38942-9
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This article presents and investigates a modified version of the Weibull distribution that incorporates four parameters and can effectively represent a hazard rate function with a shape resembling a bathtub. Its significance in the fields of lifetime and reliability stems from its ability to model both increasing and decreasing failure rates. The proposed distribution encompasses several well-known models such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh, and modified Weibull distributions. The paper derives key mathematical statistics of the proposed distribution, including the quantile function, moments, moment-generating function, and order statistics density. Various mathematical properties of the proposed model are established, and the unknown parameters of the distribution are estimated using different estimation techniques. Furthermore, the effectiveness of these estimators is assessed through numerical simulation studies. Finally, the paper applies the new model and compares it with various existing distributions by analyzing two real-life time data sets.
引用
收藏
页数:16
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