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小尾概率的区间估计——在食品安全中的应用

Interval estimation of small tail probabilities - applications in food safety.

作者信息

Kedem Benjamin, Pan Lemeng, Zhou Wen, Coelho Carlos A

机构信息

Department of Mathematics, University of Maryland, College Park, MD, U.S.A.

Department of Mathematics and Centro de Matemática e Aplicações (CMA), Faculdade de Ciências e Tecnologia (FCT/UNL), Caparica, Portugal.

出版信息

Stat Med. 2016 Aug 15;35(18):3229-40. doi: 10.1002/sim.6921. Epub 2016 Feb 17.

Abstract

Often in food safety and bio-surveillance it is desirable to estimate the probability that a contaminant or a function thereof exceeds an unsafe high threshold. The probability or chance in question is very small. To estimate such a probability, we need information about large values. In many cases, the data do not contain information about exceedingly large contamination levels, which ostensibly renders the problem insolvable. A solution is suggested whereby more information about small tail probabilities are obtained by combining the real data with computer-generated data repeatedly. This method provides short yet reliable interval estimates based on moderately large samples. An illustration is provided in terms of lead exposure data. Copyright © 2016 John Wiley & Sons, Ltd.

摘要

在食品安全和生物监测中,通常需要估计污染物或其某种功能超过不安全高阈值的概率。所讨论的概率或可能性非常小。为了估计这样的概率,我们需要关于大值的信息。在许多情况下,数据不包含关于极高污染水平的信息,这表面上使得问题无法解决。本文提出了一种解决方案,即通过反复将真实数据与计算机生成的数据相结合,来获取更多关于小尾概率的信息。该方法基于适度大的样本提供简短而可靠的区间估计。以铅暴露数据为例进行了说明。版权所有© 2016约翰·威利父子有限公司。

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