Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/77122
Authors: 
Biedermann, Stefanie
Dette, Holger
Year of Publication: 
2000
Series/Report no.: 
Technical Report, SFB 475: Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 2000,43
Abstract: 
In the common nonparametric regression model y(i) = g(ti) + a (ti) ei , i=1….,n with i.i.d - noise and nonrepeatable design points ti we consider the problem of choosing an optimal design for the estimation of the regression function g. A minimax approach is adopted which searches for designs minimizing the maximum of the asymptotic integrated mean squared error_ where the maximum is taken over an appropriately bounded class of functions (g,a). The minimax designs are found explicitly and for certain special cases the optimality of the uniform distribution can be established.
Subjects: 
Nonparametric regression
kernel estimation
locally optimal designs
minimax designs
mean squared error
Document Type: 
Working Paper

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