GENERALIZED S-ESTIMATORS

• 成果类型: Article
• 署名作者: CROUX, C; ROUSSEEUW, PJ; HOSSJER, O
• 署名单位: University of Antwerp; Lund University
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.1994.10476867
• 发表日期: 1994
• 页码: 1271-1281
• 关键词: high breakdown-point; regression; BIAS

摘要

In this article we introduce a new type of positive-breakdown regression method, called a generalized S-estimator (or GS-estimator), based on the minimization of a generalized M-estimator of residual scale. We compare the class of GS-estimators with the usual S-estimators, including least median of squares. It turns out that GS-estimators attain a much higher efficiency than S-estimators, at the cost of a slightly increased worst-case bias. We investigate the breakdown point, the maxbias curve, and the influence function of GS-estimators. We also give an algorithm for computing GS-estimators and apply it to real and simulated data.