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用对数逻辑分布的新通用改进模型来模拟 COVID-19 死亡率。

Modelling the COVID-19 Mortality Rate with a New Versatile Modification of the Log-Logistic Distribution.

机构信息

Department of Mathematics (Statistics Option) Programme, Pan African University, Institute of Basic Science, Technology and Innovation (PAUSTI), Nairobi 6200-00200, Kenya.

Department of Mathematics, Faculty of Science, Mansoura University, Mansoura 35516, Egypt.

出版信息

Comput Intell Neurosci. 2021 Nov 13;2021:8640794. doi: 10.1155/2021/8640794. eCollection 2021.

DOI:10.1155/2021/8640794
PMID:34782836
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8590594/
Abstract

The goal of this paper is to develop an optimal statistical model to analyze COVID-19 data in order to model and analyze the COVID-19 mortality rates in Somalia. Combining the log-logistic distribution and the tangent function yields the flexible extension log-logistic tangent (LLT) distribution, a new two-parameter distribution. This new distribution has a number of excellent statistical and mathematical properties, including a simple failure rate function, reliability function, and cumulative distribution function. Maximum likelihood estimation (MLE) is used to estimate the unknown parameters of the proposed distribution. A numerical and visual result of the Monte Carlo simulation is obtained to evaluate the use of the MLE method. In addition, the LLT model is compared to the well-known two-parameter, three-parameter, and four-parameter competitors. Gompertz, log-logistic, kappa, exponentiated log-logistic, Marshall-Olkin log-logistic, Kumaraswamy log-logistic, and beta log-logistic are among the competing models. Different goodness-of-fit measures are used to determine whether the LLT distribution is more useful than the competing models in COVID-19 data of mortality rate analysis.

摘要

本文旨在开发一个最优的统计模型来分析 COVID-19 数据，以便对索马里的 COVID-19 死亡率进行建模和分析。将对数逻辑分布和正切函数相结合，得到了灵活的扩展对数逻辑正切（LLT）分布，这是一种新的双参数分布。这种新分布具有许多优良的统计和数学性质，包括简单的故障率函数、可靠性函数和累积分布函数。最大似然估计（MLE）用于估计所提出分布的未知参数。通过蒙特卡罗模拟获得数值和可视化结果，以评估 MLE 方法的使用。此外，还将 LLT 模型与著名的双参数、三参数和四参数竞争模型进行了比较。竞争模型包括 Gompertz、对数逻辑、kappa、指数对数逻辑、Marshall-Olkin 对数逻辑、Kumaraswamy 对数逻辑和 beta 对数逻辑。使用不同的拟合优度度量来确定在 COVID-19 死亡率分析中，LLT 分布是否比竞争模型更有用。

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