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Variable data driven bandwidth choice in nonparametric quantile regression

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  • Klaus Abberger

    ()
    (IFO Munich)

Abstract

The choice of a smoothing parameter or bandwidth is crucial when applying non- parametric regression estimators. In nonparametric mean regression various meth- ods for bandwidth selection exists. But in nonparametric quantile regression band- width choice is still an unsolved problem. In this paper a selection procedure for local varying bandwidths based on the asymptotic mean squared error (MSE) of the local linear quantile estimator is discussed. To estimate the unknown quantities of the MSE local linear quantile regression based on cross-validation and local likeli- hood estimation is used.

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File URL: http://cofe.uni-konstanz.de/Papers/dp02_03.pdf
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Bibliographic Info

Paper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 02-03.

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Length: 13 pages
Date of creation: Jan 2002
Date of revision:
Handle: RePEc:knz:cofedp:0203

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Related research

Keywords: quantile regression; nonparametric regression; conditional quantile estimation; local linear estimation; local bandwidth selection; local likelihood; generalized logistic distribution;

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  1. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
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