Department of Statistics, University of Jeddah, College of Science, Jeddah, Saudi Arabia.
Department of Statistics, Govt. S.A Postgraduate College Dera Nawab Sahib, Bahawalpur, Punjab, Pakistan.
PLoS One. 2020 Mar 20;15(3):e0230004. doi: 10.1371/journal.pone.0230004. eCollection 2020.
In this paper, we introduce the exponentiated power generalized Weibull power series (EPGWPS) family of distributions, obtained by compounding the exponentiated power generalized Weibull and power series distributions. By construction, the new family contains a myriad of new flexible lifetime distributions having strong physical interpretations (lifetime system, biological studies…). We discuss the characteristics and properties of the EPGWPS family, including its probability density and hazard rate functions, quantiles, moments, incomplete moments, skewness and kurtosis. The main vocation of the EPGWPS family remains to be applied in a statistical setting, and data analysis in particular. In this regard, we explore the estimation of the model parameters by the maximum likelihood method, with accuracy supported by a detailed simulation study. Then, we apply it to two practical data sets, showing the applicability and competitiveness of the EPGWPS models in comparison to some other well-reputed models.
在本文中，我们引入了指数幂广义威布尔幂级数（EPGWPS）分布族，它是通过组合指数幂广义威布尔分布和幂级数分布得到的。通过构造，这个新的家族包含了许多具有强大物理解释（寿命系统、生物研究等）的新的灵活寿命分布。我们讨论了 EPGWPS 家族的特征和性质，包括它的概率密度和风险率函数、分位数、矩、不完全矩、偏度和峰度。EPGWPS 家族的主要用途仍然是在统计环境中，特别是数据分析中。在这方面，我们通过详细的模拟研究，探讨了最大似然法对模型参数的估计，为准确性提供了支持。然后，我们将其应用于两个实际数据集，展示了 EPGWPS 模型与一些其他知名模型相比在应用方面的适用性和竞争力。
