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一种新的统计分布通过 Phi-4 方程及其广泛的应用。

A new statistical distribution via the Phi-4 equation with its wide-ranging applications.

机构信息

Department of Mathematics, College of Science, Taibah University, Madinah, Saudi Arabia.

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

出版信息

PLoS One. 2024 Nov 4;19(11):e0312458. doi: 10.1371/journal.pone.0312458. eCollection 2024.

Abstract

This paper presents a new framework based on nonlinear partial differential equations and statistics. For the nonlinear Phi-4 equation, the probability density function of the hyperbolic secant (HS) distribution has been obtained. Our model's density has various shapes, including left-skewed, symmetric, and right-skewed. Eight distinct estimation approaches have been employed to estimate the parameters of our model. Additionally, the behavior of the HS model parameters was investigated using randomly generated data sets using these estimation techniques. Furthermore, we illustrate the applicability of the HS distribution for modeling real data by applying our results to real data. As a result, it is expected that our proposal will be of significant assistance to the community investigating new distributions based on hyperbolic functions and their applications to real-world data sets.

摘要

本文提出了一个基于非线性偏微分方程和统计学的新框架。对于非线性 Phi-4 方程,已经得到了双曲正割(HS)分布的概率密度函数。我们模型的密度具有各种形状,包括左偏、对称和右偏。使用了八种不同的估计方法来估计我们模型的参数。此外,还使用这些估计技术通过随机生成的数据集研究了 HS 模型参数的行为。此外,通过将我们的结果应用于实际数据,说明了 HS 分布在对基于双曲函数的真实数据进行建模方面的适用性。因此,预计我们的建议将对研究基于双曲函数的新分布及其在真实数据集应用的社区有很大帮助。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e230/11534224/293c3b1e9861/pone.0312458.g001.jpg

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