生成随机变量使用新引入的近似的累积密度下截断正态分布的模拟应用

M. Hamasha
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引用次数: 1

摘要

本文用一个简单的函数来近似下侧截断的累积正态分布,推导了该函数的逆,并说明了如何由引入的逆逼近产生随机变量。所引入的近似来源于Aludaat和Alodat的累积正态分布近似模型。采用最大绝对误差(即0.003944)对引入函数的精度进行了研究。与作者所知的所有以前的类似模型相比,这种精确度可能是最好的。
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Generate random variates using a newly introduced approximation to cumulative density of lower truncated normal distribution for simulation applications
In this paper, the lower side truncated cumulative normal distribution is approximated by a simple function, the inverse of the function is derived, and random variates are explained how to be generated from the introduced inverse approximation. The introduced approximation is derived from Aludaat and Alodat's model of approximating cumulative normal distribution. The accuracy of the introduced function is investigated in term of maximum absolute error (i.e., 0.003944). This level of accuracy is possibly the best comparing all previous similar models to the best of the author's knowledge.
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