Innovative survival modeling in pandemics with a novel family of distributions: a comparative study of UK and Mexico pandemic data

利用新型分布族构建创新型流行病生存模型:英国和墨西哥流行病数据的比较研究

阅读:2
作者:Aijaz Ahmad,Fatimah M Alghamdi,Manzoor A Khanday,Gamal A Abd-Elmougod,Getachew Tekle Mekiso,M A El-Qurashi,Ahmed M Gemeay

Abstract

Statistical approaches have broad applications in almost all areas of life, especially education, hydrology, reliability, administration, and healthcare. Statistical investigation and data forecasting are critical components of medical decision-making and outcome improvement. This article introduces an innovative generator based on the inverted trigonometric function, especially the Arccosecant Φ family of distributions, with the Burr distribution as the foundation model. This technique establishes the distributional features and adaptability of the Arccosecant-Burr distribution (for reference ACBD). The practicality of the model is demonstrated by comparing it to two datasets from the survival analysis. The first set of information indicates the fatality rate among individuals in Mexico who contracted coronavirus disease 2019 (COVID-19). The second data set shows the death rate of COVID-19 sufferers in the United Kingdom. Several estimation approaches are utilized to determine the unknown parameters of the ACBD distribution. The evaluation of these data sets reveals that the generator outperformed other models, indicating greater effectiveness.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。