Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/207
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAntoch, J.-
dc.contributor.authorJANSSEN, Paul-
dc.date.accessioned2004-08-30T07:50:50Z-
dc.date.available2004-08-30T07:50:50Z-
dc.date.issued1989-
dc.identifier.citationStatist. Prob. Letters, 8(4), p. 355-362-
dc.identifier.urihttp://hdl.handle.net/1942/207-
dc.description.abstractFor the regression model Yi = m(xi)+var epsiloni, i = 1,…,n, robust nonparametric estimators are introduced and studied in Härdle and Gasser (1984). We show that these estimators can be viewed as regression M-quantiles. We then establish a probability inequality and a Bahadur representation for such quantiles and discuss some applications.-
dc.language.isoen-
dc.subjectMathematical Statistics-
dc.subjectNon and semiparametric methods-
dc.titleNonparametric regression M-quantiles-
dc.typeJournal Contribution-
dc.identifier.epage362-
dc.identifier.issue4-
dc.identifier.spage355-
dc.identifier.volume8-
dc.bibliographicCitation.oldjcat-
dc.identifier.doi10.1016/0167-7152(89)90044-8-
item.fulltextNo Fulltext-
item.fullcitationAntoch, J. & JANSSEN, Paul (1989) Nonparametric regression M-quantiles. In: Statist. Prob. Letters, 8(4), p. 355-362.-
item.accessRightsClosed Access-
item.contributorAntoch, J.-
item.contributorJANSSEN, Paul-
Appears in Collections:Research publications
Show simple item record

SCOPUSTM   
Citations

13
checked on Oct 20, 2025

WEB OF SCIENCETM
Citations

13
checked on Oct 21, 2025

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.