The power new XLindley distribution: Statistical inference, fuzzy reliability, and applications

被引:0
|
作者
Gemeay, Ahmed M. [1 ]
Ezzebsa, Abdelali [2 ,3 ]
Zeghdoudi, Halim [2 ]
Tanis, Caner [4 ]
Tashkandy, Yusra A. [5 ]
Bakr, M. E. [5 ]
Kumar, Anoop [6 ]
机构
[1] Tanta Univ, Fac Sci, Dept Math, Tanta 31527, Egypt
[2] Badji Mokhtar Annaba Univ, LaPS Lab, Annaba, Algeria
[3] 8 May 1945 Univ, Guelma, Algeria
[4] Cankiri Karatekin Univ, Dept Stat, Cankiri, Turkiye
[5] King Saud Univ, Coll Sci, Dept Stat & Operat Res, POB 2455, Riyadh 11451, Saudi Arabia
[6] Cent Univ Haryana, Fac Basic Sci, Dept Stat, Mahendergarh 123031, India
关键词
Lindley distribution; Moments; Estimation; Fuzzy; LINDLEY DISTRIBUTION;
D O I
10.1016/j.heliyon.2024.e36594
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 paper introduces the power new XLindley (PNXL) distribution, a novel two-parameter distribution derived using the power transformation method applied to the XLindley distribution. We thoroughly explore the structural properties of the PNXL distribution, including the rth moment about the origin, moment generating function, survival rate function, distribution function, hazard rate function, skewness, kurtosis, and coefficient of variation. Additionally, we derive the quantile function, fuzzy reliability, reliability measures, stochastic ordering, and actuarial measures for this new distribution. To estimate the parameters of the PNXL distribution, we propose several estimators and evaluate their performance through extensive simulation studies. To demonstrate the applicability and superiority of the PNXL distribution over existing distributions, we fit it to two real datasets and compare its performance with potential competing models. The results highlight the PNXL distribution's effectiveness and potential as a robust tool for modeling and analyzing real-world data.
引用
收藏
页数:24
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