Nonparametric Estimation using Regression Quantiles in a Regression Model

被引：0
|
作者：
Han, Sang Moon [1 ]
Jung, Byoung Cheol [1 ]
机构：
[1] Univ Seoul, Dept Stat, 163 Siripdaero, Seoul 130743, South Korea
来源：
KOREAN JOURNAL OF APPLIED STATISTICS | 2012年 / 25卷 / 05期
关键词：
Regression quantile; regression trimmed mean; L-estimator;
D O I：
10.5351/KJAS.2012.25.5.793
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
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.
引用
收藏
页码：793 / 802
页数：10
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