Robust regression estimation based on data partitioning

  • Lee, Dong-Hee
  • Park, Yousung
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초록

We introduce a high breakdown point estimator referred to as data partitioning robust regression estimator (DPR). Since the DPR is obtained by partitioning observations into a finite number of subsets, it has no computational problem unlike the previous robust regression estimators. Empirical and extensive simulation studies show that the DPR is superior to the previous robust estimators. This is much so in large samples.

키워드

computation problemdata partitioningefficiencyhigh breakdown pointoutlier detectionperformance in large sampleHIGH BREAKDOWN-POINTLINEAR-REGRESSIONEFFICIENCYSTABILITYLOCATIONSCALEMODEL
제목
Robust regression estimation based on data partitioning
저자
Lee, Dong-HeePark, Yousung
발행일
2007-06
유형
Article
저널명
Journal of the Korean Statistical Society
36
2
페이지
299 ~ 320