Sine π-power odd-G family of distributions with applications

被引:0
|
作者
Sapkota, Laxmi Prasad [1 ]
Kumar, Pankaj [2 ]
Kumar, Vijay [2 ]
Tashkandy, Yusra A. [3 ]
Bakr, M. E. [3 ]
Balogun, Oluwafemi Samson [4 ]
Mekiso, Getachew Tekle [5 ]
Gemeay, Ahmed M. [6 ]
机构
[1] Tribhuvan Univ, Dept Stat, Tribhuvan Multiple Campus, Palpa, Nepal
[2] DDU Gorakhpur Univ, Dept Math & Stat, Gorakhpur, UP, India
[3] King Saud Univ, Coll Sci, Dept Stat & Operat Res, POB 2455, Riyadh 11451, Saudi Arabia
[4] Univ Eastern Finland, Dept Comp, FI-70211 Kuopio, Finland
[5] Wachemo Univ, Dept Stat, Hossana, Ethiopia
[6] Tanta Univ, Fac Sci, Dept Math, Tanta 31527, Egypt
来源
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
关键词
Sine family; Weibull distribution; Estimation; Cramer Rao inequality; Moment; HYPERBOLIC COSINE;
D O I
10.1038/s41598-024-69567-1
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 investigates a novel category of probability distributions and a specific member within this category. We have formulated a new family of trigonometric distributions by utilizing the odds ratio derived from the distribution function of a base distribution. This newly devised distribution family termed the "Sine pie-power odd-G family" of distributions, is constructed through a transformation involving the sine function. The paper presents an overview of the fundamental characteristics inherent to this proposed distribution family. Using the Weibull distribution as a base reference, we have introduced a member belonging to the proposed distribution family. This member demonstrates various hazard functions such as j, reverse-j, increasing, decreasing, or bathtub shapes. The paper examines essential statistical attributes of this newly introduced distribution. The estimation of the distribution's parameters is carried out via the maximum likelihood estimation method. The accuracy of the parameter estimation procedure is validated through Monte Carlo simulations. The outcomes of these simulations reveal a reduction in biases and mean square errors as sample sizes increase, even for small samples. Two sets of real-engineering data are considered to demonstrate the proposed distribution's applicability. The performance of the suggested distribution is evaluated using some model selection criteria and goodness-of-fit test statistics. Empirical evidence from these evaluations substantiates that the proposed model outperforms six existing models.
引用
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页数:18
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