Almongy Hisham M, Almetwally Ehab M, Aljohani Hassan M, Alghamdi Abdulaziz S, Hafez E H
Department of Statistics, Faculty of Commerce, Mansoura University, Mansoura, Egypt.
Department of Statistics, Faculty of Business Administration, Delta University of Science and Technology, Egypt.
Results Phys. 2021 Apr;23:104012. doi: 10.1016/j.rinp.2021.104012. Epub 2021 Mar 12.
This paper aims to model the COVID-19 mortality rates in Italy, Mexico, and the Netherlands, by specifying an optimal statistical model to analyze the mortality rate of COVID-19. A new lifetime distribution with three-parameter is introduced by a combination of Rayleigh distribution and extended odd Weibull family to produce the extended odd Weibull Rayleigh (EOWR) distribution. This new distribution has many excellent properties as simple linear representation, hazard rate function, and moment generating function. Maximum likelihood, maximum product spacing and Bayesian estimation methods are applied to estimate the unknown parameters of EOWR distribution. MCMC method is used for the Bayesian estimation. A numerical result of the Monte Carlo simulation is obtained to assess the use of estimation methods. Also, data analysis for the real data of mortality rate is considered.
本文旨在通过指定一个最优统计模型来分析新冠病毒疾病（COVID-19）的死亡率，从而对意大利、墨西哥和荷兰的COVID-19死亡率进行建模。通过瑞利分布和扩展奇韦布尔族的组合引入了一种新的三参数寿命分布，以产生扩展奇韦布尔瑞利（EOWR）分布。这种新分布具有许多优良特性，如简单线性表示、风险率函数和矩生成函数。应用最大似然法、最大乘积间距法和贝叶斯估计方法来估计EOWR分布的未知参数。贝叶斯估计采用马尔可夫链蒙特卡罗（MCMC）方法。获得了蒙特卡罗模拟的数值结果，以评估估计方法的使用情况。此外，还考虑了对死亡率实际数据的数据分析。
