Online Resource
Berlin : Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
Format:
1 Online-Ressource (20 Seiten)
ISSN:
1436-1086
Series Statement:
2002,88
Content:
The Nadaraya-Watson estimator of regression is known to be highly sensitive to the presence of outliers in the sample. A possible way of robustication consists in using local L-estimates of regression. Whereas the local L-estimation is traditionally done using an empirical conditional distribution function, we propose to use instead a smoothed conditional distribution function. We show that this smoothed L-estimation approach provides computational as well as statistical finite sample improvements. The asymptotic distribution of the estimator is derived under mild β-mixing conditions.
Language:
English
URN:
urn:nbn:de:kobv:11-10049692
URL:
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