Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/22561 
Erscheinungsjahr: 
2004
Schriftenreihe/Nr.: 
Technical Report No. 2004,48
Verlag: 
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, Dortmund
Zusammenfassung: 
In this note we consider several goodness-of-fit tests for model specification in non- parametric regression models which are based on kernel methods. In order to circumvent the problem of choosing a bandwidth for the corresponding test statistic we propose to consider the statistics as stochastic processes indexed with bandwidths proportional to the asymptotically optimal bandwidth for the estimation of the regression function. We prove weak convergence of these processes to centered Gaussian processes and suggest to use functionals of these processes as test statistics for the problem of model specification. A bootstrap test is proposed to obtain a good approximation of the nominal level. The results are illustrated by means of a simulation study and the new test is compared with some of the currently available procedures.
Schlagwörter: 
goodness-of-fit test
weak convergence
nonparametric regression
specification test
selection of smoothing parameters
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
159.09 kB
319.06 kB





Publikationen in EconStor sind urheberrechtlich geschützt.