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A NEW PERSPECTIVE ON ROBUST M-ESTIMATION: FINITE SAMPLE THEORY AND APPLICATIONS TO DEPENDENCE-ADJUSTED MULTIPLE TESTING()

Heavy-tailed errors impair the accuracy of the least squares estimate, which can be spoiled by a single grossly outlying observation. As argued in the seminal work of Peter Huber in 1973 [Ann. Statist. 1 (1973) 799–821], robust alternatives to the method of least squares are sorely needed. To achiev...

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Detalles Bibliográficos
Publicado en:Ann Stat
Main Authors: Zhou, Wen-Xin, Bose, Koushiki, Fan, Jianqing, Liu, Han
Formato: Artigo
Idioma:Inglês
Publicado: 2018
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Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC6133288/
https://ncbi.nlm.nih.gov/pubmed/30220745
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/17-AOS1606
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