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Variable data driven bandwidth choice in nonparametric quantile regression

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  • Abberger, Klaus

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.

Suggested Citation

  • Abberger, Klaus, 2002. "Variable data driven bandwidth choice in nonparametric quantile regression," CoFE Discussion Papers 02/03, University of Konstanz, Center of Finance and Econometrics (CoFE).
    • Handle: RePEc:zbw:cofedp:0203
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    References listed on IDEAS

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

    1. Mercedes Conde-Amboage & César Sánchez-Sellero, 2019. "A plug-in bandwidth selector for nonparametric quantile regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 423-450, June.

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