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dc.contributor.authorJeong, Seok-Ohen_US
dc.contributor.authorPark, Byeong U.en_US
dc.description.abstractGiven n independent and identically distributed observations in a set G with an unknown function g, called a boundary or frontier, it is desired to estimate g from the observations. The problem has several important applications including classification and cluster analysis, and is closely related to edge estimation in image reconstruction. It is particularly important in econometrics. The convex-hull estimator of a boundary or frontier is very popular in econometrics, where it is a cornerstone of a method known as `data envelope analysis´ or DEA. In this paper we give a large sample approximation of the distribution of the convex-hull estimator in the general case where p>=1. We discuss ways of using the large sample approximation to correct the bias of the convex-hull and the DEA estimators and to construct confidence intervals for the true function.en_US
dc.relation.ispartofseries|aPapers / Humboldt-Universität Berlin, Center for Applied Statistics and Economics (CASE) |x2004,39en_US
dc.subject.keywordfree disposal hullen_US
dc.subject.keywordfrontier functionen_US
dc.subject.keyworddata envelope analysisen_US
dc.subject.keywordproductivity analysisen_US
dc.subject.keywordrate of convergenceen_US
dc.titleLimit Distribution of Convex-Hull Estimators of Boundariesen_US
dc.typeWorking Paperen_US

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