Nonparametric quantile regression for twice censored data

dc.contributor.author	Dette, Holger	de
dc.contributor.author	Volgushev, Stanislav	de
dc.date.accessioned	2009-10-29T10:23:21Z
dc.date.available	2009-10-29T10:23:21Z
dc.date.issued	2009-09-16	de
dc.description.abstract	We consider the problem of nonparametric quantile regression for twice censored data. Two new estimates are presented, which are constructed by applying concepts of monotone rearrangements to estimates of the conditional distribution function. The proposed methods avoid the problem of crossing quantile curves. Weak uniform consistency and weak convergence is established for both estimates and their finite sample properties are investigated by means of a simulation study. As a by-product, we obtain a new result regarding the weak convergence of the Beran estimator for right censored data on the maximal possible domain, which is of its own interest.	en
dc.identifier.uri	http://hdl.handle.net/2003/26495
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-12665
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823; 23/2009	de
dc.subject	Beran estimator	en
dc.subject	censored data	en
dc.subject	crossing quantile curves	en
dc.subject	monotone rearrangements	en
dc.subject	quantile regression	en
dc.subject	survival analysis	en
dc.subject.ddc	310	de
dc.subject.ddc	330	de
dc.subject.ddc	620	de
dc.title	Nonparametric quantile regression for twice censored data	en
dc.type	Text	de
dc.type.publicationtype	report	de
dcterms.accessRights	open access

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