Local Linear Additive Quantile Regression

Local Linear Additive Quantile Regression Abstract. We consider non‐parametric additive quantile regression estimation by kernel‐weighted local linear fitting. The estimator is based on localizing the characterization of quantile regression as the minimizer of the appropriate ‘check function’. A backfitting algorithm and a heuristic rule for selecting the smoothing parameter are explored. We also study the estimation of average‐derivative quantile regression under the additive model. The techniques are illustrated by a simulated example and a real data set. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Scandinavian Journal of Statistics Wiley

Local Linear Additive Quantile Regression

Scandinavian Journal of Statistics, Volume 31 (3) – Sep 1, 2004

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Publisher
Wiley
Copyright
Copyright © 2004 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0303-6898
eISSN
1467-9469
DOI
10.1111/j.1467-9469.2004.03_035.x
Publisher site
See Article on Publisher Site

Abstract

Abstract. We consider non‐parametric additive quantile regression estimation by kernel‐weighted local linear fitting. The estimator is based on localizing the characterization of quantile regression as the minimizer of the appropriate ‘check function’. A backfitting algorithm and a heuristic rule for selecting the smoothing parameter are explored. We also study the estimation of average‐derivative quantile regression under the additive model. The techniques are illustrated by a simulated example and a real data set.

Journal

Scandinavian Journal of StatisticsWiley

Published: Sep 1, 2004

References

  • Quantile smooth splines
    Koenker, Koenker; Ng, Ng; Portnoy, Portnoy
  • Local linear quantile regression
    Yu, Yu; Jones, Jones

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