Variable data driven bandwidth choice in nonparametric quantile regression
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.
|Date of creation:||Jan 2002|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://cofe.uni-konstanz.de
More information through EDIRC
|Order Information:|| Web: http://cofe.uni-konstanz.de Email: |
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
When requesting a correction, please mention this item's handle: RePEc:knz:cofedp:0203. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ingmar Nolte)The email address of this maintainer does not seem to be valid anymore. Please ask Ingmar Nolte to update the entry or send us the correct address
If references are entirely missing, you can add them using this form.