Modifying the double smoothing bandwidth selector in nonparametric regression

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2000
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Zusammenfassung

In this paper a modified double smoothing bandwidth selector, ^h MDS , based on a new criterion, which combines the plug-in and the double smoothing ideas, is proposed. A self-complete iterative double smoothing rule ( ^ h IDS ) is introduced as a pilot method. The asymptotic properties of both ^ h IDS and ^ h MDS are investigated. It is shown that ^ h MDS performs asymptotically very well. Moreover, it is asymptotically negatively correlated with h ASE , the minimizer of the averaged squared error. The asymptotic performances of ^ h MDS and of the iterative plug-in method, ^ h IPL (Gasser et al., 1991) are compared. A comparative simulation study is carried out to show the practical performance of ^ h MDS and related methods. It is shown that ^ h MDS seems to be the best in the practice. Finite sample negative correlations between the chosen bandwidth selectors and h ASE are also studied.

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Fachgebiet (DDC)
330 Wirtschaft
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Bandwidth selection, double smoothing, nonparametric regression, plug-in
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ISO 690BERAN, Jan, Yuanhua FENG, Siegfried HEILER, 2000. Modifying the double smoothing bandwidth selector in nonparametric regression
BibTex
@techreport{Beran2000Modif-650,
  year={2000},
  series={CoFE-Diskussionspapiere / Zentrum für Finanzen und Ökonometrie},
  title={Modifying the double smoothing bandwidth selector in nonparametric regression},
  number={2000/37},
  author={Beran, Jan and Feng, Yuanhua and Heiler, Siegfried}
}
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    <dcterms:abstract xml:lang="eng">In this paper a modified double smoothing bandwidth selector, ^h MDS , based on a new criterion, which combines the plug-in and the double smoothing ideas, is proposed. A self-complete iterative double smoothing rule ( ^ h IDS ) is introduced as a pilot method. The asymptotic properties of both ^ h IDS and ^ h MDS are investigated. It is shown that ^ h MDS performs asymptotically very well. Moreover, it is asymptotically negatively correlated with h ASE , the minimizer of the averaged squared error. The asymptotic performances of ^ h MDS and of the iterative plug-in method, ^ h IPL (Gasser et al., 1991) are compared. A comparative simulation study is carried out to show the practical performance of ^ h MDS and related methods. It is shown that ^ h MDS seems to be the best in the practice. Finite sample negative correlations between the chosen bandwidth selectors and h ASE are also studied.</dcterms:abstract>
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