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Interval estimation of small tail probabilities – applications in food safety
Author(s) -
Kedem Benjamin,
Pan Lemeng,
Zhou Wen,
Coelho Carlos A.
Publication year - 2016
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6921
Subject(s) - computer science , interval (graph theory) , statistics , probability estimation , estimation , probability and statistics , function (biology) , econometrics , data mining , mathematics , artificial intelligence , combinatorics , management , evolutionary biology , economics , biology
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.