Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/143
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dc.contributor.authorVERAVERBEKE, Noel-
dc.date.accessioned2004-08-26T14:43:20Z-
dc.date.available2004-08-26T14:43:20Z-
dc.date.issued1987-
dc.identifier.citationStatistics and Probability Letters, 5(3), p. 175-180-
dc.identifier.urihttp://hdl.handle.net/1942/143-
dc.description.abstractLet HF be the distribution function of h(X1,…,Xm), where h is a real valued function of m variables and X1,…,Xn (n gt-or-equal, slanted m) is an i.i.d. sample from a distribution function F. A kernel-type estimator is proposed for the generalized quantile H−1F (p) (0 < p < 1). Under fairly general conditions we establish asymptotic normality of the estimator and consistent estimation of its asymptotic variance.-
dc.language.isoen-
dc.subjectMathematical Statistics-
dc.subjectNon and semiparametric methods-
dc.titleA kernel-type estimator for generalized quantiles-
dc.typeJournal Contribution-
dc.identifier.epage180-
dc.identifier.issue3-
dc.identifier.spage175-
dc.identifier.volume5-
dc.bibliographicCitation.oldjcat-
dc.identifier.doi10.1016/0167-7152(87)90034-4-
item.fullcitationVERAVERBEKE, Noel (1987) A kernel-type estimator for generalized quantiles. In: Statistics and Probability Letters, 5(3), p. 175-180.-
item.fulltextNo Fulltext-
item.contributorVERAVERBEKE, Noel-
item.accessRightsClosed Access-
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