dc.contributor.author | Györfi, László | |
dc.contributor.author | Walk, Harro | |
dc.date.accessioned | 2015-05-18T12:00:00Z | |
dc.date.accessioned | 2016-10-05T14:14:23Z | |
dc.date.available | 2015-05-18T12:00:00Z | |
dc.date.available | 2016-10-05T14:14:23Z | |
dc.date.issued | 2012 | |
dc.identifier.uri | http://publications.mfo.de/handle/mfo/1210 | |
dc.description | Research in Pairs 2012 | en_US |
dc.description.abstract | Consider the regression problem with a response variable $Y$ and with a $d$-dimensional feature vector $X$. For the regression function $m(x) = \mathbb{E}\{Y|X = x\}$, this paper investigates methods for estimating the density of the residual $Y -m(X)$ from independent and identically distributed data. For heteroscedastic regression, we prove the strong universal (density-free) $L_1$-consistency of a recursive and a nonrecursive kernel density estimate based on a regression estimate. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Mathematisches Forschungsinstitut Oberwolfach | en_US |
dc.relation.ispartofseries | Oberwolfach Preprints;2012,07 | |
dc.subject | Regression residual | en_US |
dc.subject | Nonparametric kernel density estimation | en_US |
dc.subject | Nonparametric regression estimation | en_US |
dc.subject | Heteroscedastic regression | en_US |
dc.title | Strongly Consistent Density Estimation of Regression Redidual | en_US |
dc.type | Preprint | en_US |
dc.rights.license | Dieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. | de |
dc.rights.license | This document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties. | en |
dc.identifier.doi | 10.14760/OWP-2012-07 | |
local.scientificprogram | Research in Pairs 2012 | |
local.series.id | OWP-2012-07 | |
local.subject.msc | 62 | |
dc.identifier.urn | urn:nbn:de:101:1-201207047025 | |
dc.identifier.ppn | 1651531307 | |