응용통계연구 (The Korean Journal of Applied Statistics)

  • 제25권5호
  • /
  • Pages.793-802
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  • 2012
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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Nonparametric Estimation using Regression Quantiles in a Regression Model

  • 투고 : 2012.08.11
  • 심사 : 2012.09.21
  • 발행 : 2012.10.31
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초록

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.

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참고문헌

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