절사가 주어질때 회귀기울기의 점근적 최량 L-추정법

Asymptotically Efficient L-Estimation for Regression Slope When Trimming is Given

  • Sang Moon Han (Department of Computer Science and Statistics, Seoul City University, 90 Jeonnong Dong, Dongdeamoon ku, Seoul, Korea)
  • 발행 : 1994.09.01

초록

Han(1993)의 임의의 오차분포하에서 회귀모형에의 기울기 추정법을 응용하여 회귀분위선(regression quantile)에 의해 적당한 상.하위절사가 주어질 때 점근적으로 최량의 회귀모형에서의 기울기 추정량을 구성할 수 있음을 보였다.

By applying slope estimator under the arbitrary error distributions proposed by Han(1993), if we define regression quantiles to give upper and lower trimming part and blocks of data, we show the proposed slope estimator has asymptotically efficient slope estimator when the number of regression quantiles to from blocks of data goes to sufficiently large.

키워드

참고문헌

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