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用于对实际数据建模的统一指数 - H 族:性质与推断。

A unified exponential-H family for modeling real-life data: Properties and inference.

作者信息

Jamal Farrukh, Alqawba Mohammed, Altayab Yasser, Iqbal Tariq, Afify Ahmed Z

机构信息

Department of Statistics, The Islamia University Bahawalpur, 63100, Pakistan.

Department of Mathematics, College of Science, Qassim University, Buraydah 51452, Saudi Arabia.

出版信息

Heliyon. 2024 Mar 12;10(6):e27661. doi: 10.1016/j.heliyon.2024.e27661. eCollection 2024 Mar 30.

Abstract

The exponential distribution is one of the most widely used statistical distribution for reliability issues. In this paper, we introduce a novel family based on the exponential model, called the new exponential-H (NEx-H) family. The sub-models of the NEx-H family are capable of accommodating variable failure rates, as well as unimodal, bimodal, left-skewed, symmetric, right-skewed, and J-shape densities. The mathematical features of the NEx-H family are derived. The parameters of the NEx-Weibull distribution are estimated by using seven estimation methods. Detailed numerical simulations are presented. Based on our study, the maximum likelihood is the best estimation method for estimating the NEx-Weibull parameters. Three real-life data sets are fitted using the NEx-Weibull distribution. The NEx-Weibull model provides better fit as compared to some competing Weibull models.

摘要

指数分布是可靠性问题中使用最广泛的统计分布之一。在本文中,我们引入了一个基于指数模型的新族,称为新指数 - H(NEx - H)族。NEx - H族的子模型能够适应可变失效率,以及单峰、双峰、左偏、对称、右偏和J形密度。推导了NEx - H族的数学特征。使用七种估计方法估计了NEx - 威布尔分布的参数。给出了详细的数值模拟。基于我们的研究,最大似然法是估计NEx - 威布尔参数的最佳估计方法。使用NEx - 威布尔分布对三个实际数据集进行了拟合。与一些竞争的威布尔模型相比,NEx - 威布尔模型提供了更好的拟合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3271/10951600/39f493178c1a/gr001.jpg

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