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广义双参数分布:统计性质、估计及其在 COVID-19 中的应用。

General two-parameter distribution: Statistical properties, estimation, and application on COVID-19.

机构信息

Department of Mathematics, Faculty of Science, Tanta University, Tanta, Egypt.

LaPS laboratory, Badji mokhtar University, Annaba, Algeria.

出版信息

PLoS One. 2023 Feb 8;18(2):e0281474. doi: 10.1371/journal.pone.0281474. eCollection 2023.

Abstract

In this paper, we introduced a novel general two-parameter statistical distribution which can be presented as a mix of both exponential and gamma distributions. Some statistical properties of the general model were derived mathematically. Many estimation methods studied the estimation of the proposed model parameters. A new statistical model was presented as a particular case of the general two-parameter model, which is used to study the performance of the different estimation methods with the randomly generated data sets. Finally, the COVID-19 data set was used to show the superiority of the particular case for fitting real-world data sets over other compared well-known models.

摘要

在本文中,我们介绍了一种新的通用双参数统计分布,它可以表示为指数分布和伽马分布的混合。从数学上推导了一般模型的一些统计性质。许多估计方法研究了提出的模型参数的估计。作为一般双参数模型的特例,提出了一个新的统计模型,用于使用随机生成的数据集研究不同估计方法的性能。最后,使用 COVID-19 数据集来显示特定案例在拟合实际数据集方面相对于其他比较知名模型的优越性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc19/9907847/216316d9d83a/pone.0281474.g001.jpg

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