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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...
Gorde:
| Argitaratua izan da: | Ann Stat |
|---|---|
| Egile Nagusiak: | , , , |
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
2018
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| Gaiak: | |
| Sarrera elektronikoa: | 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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