Gemeay Ahmed M, Ezzebsa Abdelali, Zeghdoudi Halim, Tanış Caner, Tashkandy Yusra A, Bakr M E, Kumar Anoop
Department of Mathematics, Faculty of Science, Tanta University, Tanta 31527, Egypt.
LaPS laboratory, Badji Mokhtar -Annaba University, Annaba, Algeria and 8 May 1945 University, Guelma, Algeria.
Heliyon. 2024 Aug 22;10(17):e36594. doi: 10.1016/j.heliyon.2024.e36594. eCollection 2024 Sep 15.
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 th 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.
本文介绍了幂新XLindley（PNXL）分布，这是一种通过对XLindley分布应用幂变换方法得到的新型双参数分布。我们深入探讨了PNXL分布的结构特性，包括原点矩、矩生成函数、生存率函数、分布函数、危险率函数、偏度、峰度和变异系数。此外，我们还推导了该新分布的分位数函数、模糊可靠性、可靠性度量、随机序和精算度量。为了估计PNXL分布的参数，我们提出了几种估计器，并通过广泛的模拟研究评估了它们的性能。为了证明PNXL分布相对于现有分布的适用性和优越性，我们将其拟合到两个真实数据集，并将其性能与潜在的竞争模型进行比较。结果突出了PNXL分布作为一种用于建模和分析实际数据的强大工具的有效性和潜力。
