Authors: Davies, P. L.
Gather, U.
Weinert, H.
Title: Nonparametric regression as an example of model choice
Language (ISO): en
Abstract: Nonparametric regression can be considered as a problem of model choice. In this paper we present the results of a simulation study in which several nonparametric regression techniques including wavelets and kernel methods are compared with respect to their behaviour on different test beds. We also include the taut-string method whose aim is not to minimize the distance of an estimator to some “true” generating function f but to provide a simple adequate approximation to the data. Test beds are situations where a “true” generating f exists and in this situation it is possible to compare the estimates of f with f itself. The measures of performance we use are the L^2 and the L^infinity norms and the ability to identify peaks.
Subject Headings: Kernel method
Nonparametric regression
Simulation study
Taut string method
Issue Date: 2006-05-04T09:55:49Z
Appears in Collections:Sonderforschungsbereich (SFB) 475

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