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https://hdl.handle.net/10419/65369
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tamine, Julien | en |
dc.date.accessioned | 2012-10-19T10:25:37Z | - |
dc.date.available | 2012-10-19T10:25:37Z | - |
dc.date.issued | 2001 | - |
dc.identifier.pi | urn:nbn:de:kobv:11-10049243 | en |
dc.identifier.uri | http://hdl.handle.net/10419/65369 | - |
dc.description.abstract | In this work, we introduce a smoothed influence function that constitute a theoretical tool for studying the outliers robustness properties of a large class of nonparametric estimators. With this tool, we first show the nonrobustness of the Nadaraya-Watson estimator of regression. Then we show that the M, the L and the R-estimators of the regression achieve robustness (when estimated by kernel). Our results are illustrated performing Monte-Carlo simulation. | en |
dc.language.iso | eng | en |
dc.publisher | |aHumboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes |cBerlin | en |
dc.relation.ispartofseries | |aSFB 373 Discussion Paper |x2002,62 | en |
dc.subject.jel | C13 | en |
dc.subject.jel | C14 | en |
dc.subject.jel | C15 | en |
dc.subject.ddc | 330 | en |
dc.subject.keyword | robustness | en |
dc.subject.keyword | nonparametric regression | en |
dc.subject.keyword | influence function | en |
dc.subject.keyword | M-estimator | en |
dc.subject.keyword | L-estimator | en |
dc.subject.keyword | R-estimator | en |
dc.subject.keyword | Von-mises statistical functional generalized Delta-theorem | en |
dc.title | Smoothed influence function: Another view at robust nonparametric regression | - |
dc.type | Working Paper | en |
dc.identifier.ppn | 727037854 | en |
dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | en |
dc.identifier.repec | RePEc:zbw:sfb373:200262 | en |
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