估计职业暴露的平均值。

X H Zhou
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引用次数: 4

摘要

对对数正态分布职业暴露的均值提供一个准确的估计是非常重要的。估计对数正态均值的四种常用方法是样本均值、最大似然估计(MLE)、偏差校正的最大似然估计(MLE)和最小方差无偏估计(MVUE)。本文给出了这四种估计器的均方误差的显式表达式,并从均方误差的角度比较了这四种估计器的性能。本文重申了早期研究者的结论,即MVUE一致优于其他三种估计值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating the mean value of occupational exposures.

It is very important to provide an accurate estimate for the mean value of lognormal distributed occupational exposures. Four commonly used methods for estimating a lognormal mean are the sample mean, the maximum likelihood estimate (MLE), a bias-corrected MLE, and the minimum variance unbiased estimator (MVUE). In this article the explicit expressions are given for the mean square errors of these four estimators, and performances of these four estimators are compared in terms of their mean square errors. This article reaffirms the conclusion of earlier researchers that the MVUE is uniformly superior to the other three estimators.

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