Nonparametric regression as an example of model choice

Arbeitspapier

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 L2 and the L1 norms and the ability to identify peaks.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Technical Report ; No. 2006,24

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Davies, Paul Lyndon ; Gather, Ursula ; Weinert, Henrike
• Event: Veröffentlichung
• (who): Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
• (where): Dortmund
• (when): 2006

Further information

• Handle: http://hdl.handle.net/10419/22667
• Last update: 10.03.2025, 11:44 AM CET