Optimal designs for quantile regression models

dc.contributor.author	Dette, Holger
dc.contributor.author	Trampisch, Matthias
dc.date.accessioned	2011-08-11T13:15:24Z
dc.date.available	2011-08-11T13:15:24Z
dc.date.issued	2011-08-11
dc.description.abstract	Despite of their importance optimal designs for quantile regression models have not been developed so far. In this paper we investigate the D-optimal design problem for the location scale nonlinear quantile regression model. We provide a necessary condition to check for the optimality of a given design and use it to determine bounds for the number of support points of locally D-optimal designs. The results are illustrated determining locally, Bayesian and standardized maximin D-optimal designs for quantile regression analysis in the Michaelis-Menten and EMAX model, where the location and the scale function are related by a known link function.	en
dc.identifier.uri	http://hdl.handle.net/2003/28973
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-12655
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823;26/2011
dc.subject	EMAX model	en
dc.subject	heteroscedasticity	en
dc.subject	locally optimal design	en
dc.subject	Michaelis-Menten model	en
dc.subject	quantile regression	en
dc.subject	robust designs	en
dc.subject.ddc	310
dc.subject.ddc	330
dc.subject.ddc	620
dc.title	Optimal designs for quantile regression models	en
dc.type	Text	de
dc.type.publicationtype	workingPaper	de
dcterms.accessRights	open access

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