title: Interval estimation of small tail probabilities - applications in food safety.
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.
authors.affiliation: Department of Mathematics, University of Maryland, College Park, MD, U.S.A.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Kedem
authors.affiliation: Department of Mathematics, University of Maryland, College Park, MD, U.S.A.
authors.forename: Lemeng
authors.initials: L
authors.lastname: Pan
authors.affiliation: Department of Mathematics, University of Maryland, College Park, MD, U.S.A.
authors.forename: Wen
authors.initials: W
authors.lastname: Zhou
authors.affiliation: Department of Mathematics and Centro de Matemática e Aplicações (CMA), Faculdade de Ciências e Tecnologia (FCT/UNL), Caparica, Portugal.
authors.forename: Carlos A
authors.initials: CA
authors.lastname: Coelho
mesh_terms: D059022:Food Safety; D011336:Probability
keywords: NHANES; coverage; density ratio model; food safety; out of sample fusion; semiparametric