On the breakdown point of multivariate location estimators based on trimming procedures

DOI10.1016/0167-7152(91)90186-UzbMath0732.62051OpenAlexW2088187939MaRDI QIDQ808584

Alfonso Gordaliza

Publication date: 1991

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(91)90186-u

zbMATH Keywords

finite sample breakdown pointsimpartial trimmed meanslocation estimatorstrimmed Chebyshev centrestrimming procedures

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items

Trimmed \(k\)-means: An attempt to robustify quantizers ⋮ Trimmed best \(k\)-nets: A robustified version of an \(L_{\infty}\)-based clustering method ⋮ A robust approach to model-based classification based on trimming and constraints. Semi-supervised learning in presence of outliers and label noise ⋮ A Robust Maximal F-Ratio Statistic to Detect Clusters Structure ⋮ Breakdown and groups. (With discussions and rejoinder) ⋮ Asymptotics for trimmed \(k\)-means and associated tolerance zones.

Cites Work

• On M and P estimators that have breakdown point equal to 1/2
• Least Median of Squares Regression
• A General Qualitative Definition of Robustness
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