MINIMUM DISPARITY ESTIMATION IN THE ERRORS-IN-VARIABLES MODEL

被引：10
|
作者：
BASU, A
SARKAR, S
机构：
[1] UNIV TEXAS,DEPT MATH,AUSTIN,TX 78712
[2] OKLAHOMA STATE UNIV,DEPT STAT,STILLWATER,OK 74078
来源：
STATISTICS & PROBABILITY LETTERS | 1994年 / 20卷 / 01期
关键词：
HELLINGER DISTANCE; KERNEL DENSITY ESTIMATION; ROBUSTNESS; TRANSPARENT KERNEL;
D O I：
10.1016/0167-7152(94)90236-4
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：
Robust estimators are determined using the minimum disparity estimation method (Lindsay, 1994; Basu and Lindsay, 1994) in the errors-in-variables model. These estimators are asymptotically fully efficient for the model considered and have strong robustness features. In a numerical example these estimators compare favorably with the orthogonal regression M-estimators of Zamar (1989).
引用
收藏
页码：69 / 73
页数：5
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