Nonparametric Estimation using Regression Quantiles in a Regression Model

  • Received : 2012.08.11
  • Accepted : 2012.09.21
  • Published : 2012.10.31


One proposal is made to construct a nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of the idea of minimizing approximate variance of a proposed estimator using regression quantiles. This nonparametric estimator and some other L-estimators are studied and compared with well known M-estimators through a simulation study.


Regression quantile;regression trimmed mean;L-estimator


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Supported by : University of Seoul