|Authors:||Davies, P. L.|
|Title:||Nonparametric regression as an example of model choice|
|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|
Taut string method
|Appears in Collections:||Sonderforschungsbereich (SFB) 475|
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