On the Generalized Power Transformation of Left Truncated Normal Distribution

C. Okoli, D. F. Nwosu, G. A. Osuji, N A Nsiegbe
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Abstract

In this study, we considered various transformation problems for a left-truncated normal distribution recently announced by several researchers and then possibly seek to establish a unified approach to such transformation problems for certain type of random variable and their associated probability density functions in the generalized setting. The results presented in this research, actually unify, improve and as well trivialized the results recently announced by these researchers in the literature, particularly for a random variable that follows a left-truncated normal distribution. Furthermore, we employed the concept of approximation theory to establish the existence of the optimal value y_max in the interval denoted by (σ_a,σ_b) ((σ_p,σ_q)) corresponding to the so-called interval of normality estimated by these authors in the literature using the Monte carol simulation method.
关于左截断正态分布的广义幂变换
在本研究中,我们考虑了最近几位研究者提出的左截断正态分布的各种变换问题,然后可能寻求在广义设置下对某类型随机变量及其相关概率密度函数的这种变换问题建立统一的方法。这项研究的结果实际上统一、改进并简化了这些研究人员最近在文献中宣布的结果,特别是对于遵循左截尾正态分布的随机变量。在此基础上,利用逼近理论的概念,建立了在(σ_a,σ_b) ((σ_p,σ_q))区间内最优值y_max的存在性,该区间对应于这些作者用Monte carol模拟法估计的所谓正态性区间。
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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