Statistical Hybridization of Normal and Weibull Distributions with its Properties and Applications

Oyetunde Aa
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Abstract

The normal distribution is one of the most popular probability distributions with applications to real life data. In this research paper, an extension of this distribution together with Weibull distribution called the Weimal distribution which is believed to provide greater flexibility to model scenarios involving skewed data was proposed. The probability density function and cumulative distribution function of the new distribution can be represented as a linear combination of exponential normal density functions. Analytical expressions for some mathematical quantities comprising of moments, moment generating function, characteristic function and order statistics were presented. The estimation of the proposed distribution’s parameters was undertaken using the method of maximum likelihood estimation. Two data sets were used for illustration and performance evaluation of the proposed model. The results of the comparative analysis to other baseline models show that the proposed distribution would be more appropriate when dealing with skewed data.
正态分布和威布尔分布的统计杂交及其性质和应用
正态分布是应用于实际生活数据的最流行的概率分布之一。在本研究中,提出了该分布与威布尔分布的扩展,称为威姆分布,该分布被认为可以为涉及偏斜数据的场景建模提供更大的灵活性。新分布的概率密度函数和累积分布函数可以表示为指数正态密度函数的线性组合。给出了由矩、矩生成函数、特征函数和阶统计量组成的数学量的解析表达式。采用极大似然估计方法对所提出的分布参数进行估计。使用两个数据集对所提出的模型进行了说明和性能评估。与其他基线模型的对比分析结果表明,所提出的分布在处理偏态数据时更为合适。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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