Efficient estimation of the error distribution function in heteroskedastic nonparametric regression with missing data

dc.contributor.author	Chown, Justin
dc.date.accessioned	2016-10-14T10:22:43Z
dc.date.available	2016-10-14T10:22:43Z
dc.date.issued	2016
dc.description.abstract	We propose a residual-based empirical distribution function to estimate the distribution function of the errors of a heteroskedastic nonparametric regression with responses missing at random based on completely observed data, and we show this estimator is asymptotically most precise.	en
dc.identifier.uri	http://hdl.handle.net/2003/35285
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-17328
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB823;51, 2016	en
dc.subject	heteroskedastic	en
dc.subject	empirical distribution function	en
dc.subject	efficient estimator	en
dc.subject	transfer principle	en
dc.subject	local polynomial smoother	en
dc.subject	nonparametric regression	en
dc.subject.ddc	310
dc.subject.ddc	330
dc.subject.ddc	620
dc.subject.rswk	Fehlerabschätzung	de
dc.subject.rswk	Heteroskedastizität	de
dc.subject.rswk	Nichtparametrische Regression	de
dc.title	Efficient estimation of the error distribution function in heteroskedastic nonparametric regression with missing data	en
dc.type	Text	de
dc.type.publicationtype	workingPaper	de
dcterms.accessRights	open access

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