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Local Linear Additive Quantile Regression

Keming Yu and Zudi Lu

Scandinavian Journal of Statistics, 2004, vol. 31, issue 3, 333-346

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.

Date: 2004
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Citations: View citations in EconPapers (28)

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https://doi.org/10.1111/j.1467-9469.2004.03_035.x

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