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Robust Estimators are Hard to Compute
In modern statistics, the robust estimation of parameters of a regression hyperplane is a central problem. Robustness means that the estimation is not or only slightly affected by outliers in the data. In this paper, it is shown that the following robust estimators are hard to compute: LMS, LQS, LTS, LTA, MCD, MVE, Constrained M estimator, Projection Depth (PD) and Stahel-Donoho. In addition, a...
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ژورنال
عنوان ژورنال: Theoretical Computer Science
سال: 1980
ISSN: 0304-3975
DOI: 10.1016/0304-3975(80)90020-1