Maximum bias curves for robust regression with non-elliptical regressors

被引:13
作者
Berrendero, JR
Zamar, RH
机构
[1] Univ Autonoma Madrid, Dept Matemat, E-28049 Madrid, Spain
[2] Univ British Columbia, Dept Stat, Vancouver, BC V6T 1Z2, Canada
关键词
robust regression; maxbias curve; S-estimates; tau-estimates; R-estimates;
D O I
10.1214/aos/996986507
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
Maximum bias curves for some regression estimates were previously derived assuming that (i) the intercept term is known and/or (ii) the regressors have an elliptical distribution. We present a single method to obtain the maximum bias curves for a large class of regression estimates. Our results are derived under very mild conditions and, in particular, do not require the restrictive assumptions (i) and (ii) above. Using these results it is shown that the maximum bias curves heavily depend on the shape of the regressors' distribution which we call the x-configuration. Despite this big effect, the relative performance of different estimates remains unchanged under different x-configurations. We also explore the links between maxbias curves acid bias bounds. Finally, we compare the robustness properties of some estimates for the intercept parameter.
引用
收藏
页码:224 / 251
页数:28
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