Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/77227 
Year of Publication: 
2000
Series/Report no.: 
Technical Report No. 2000,41
Publisher: 
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, Dortmund
Abstract: 
For the problem of checking linearity in a heteroscedastic nonparametric regression model under a fixed design assumption we study maximin designs which maximize the minimum power of a nonparametric test over a broad class of alternatives from the assumed linear regression model. It is demonstrated that the optimal design depends sensitively on the used estimation technique (i.e. weighted or ordinary least squares) and on an inner product used in the definiton of the class of alternatives. Our results extend and put recent finndings of Wiens (1991) in a new light, who established the maximin optimality of the uniform design for lack-of-fit tests in homoscedastic multiple linear regression models.
Subjects: 
goodness-of-fit test
weighted least squares
optimal design
maximin optimality
D1-optimality
Document Type: 
Working Paper

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