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

页码：69 / 73

页数：5

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