Multivariate trimmed means based on the Tukey depth

DOI10.1016/j.jspi.2008.03.038zbMath1149.62045OpenAlexW2033915525MaRDI QIDQ958794

Jean-Claude Massé

Publication date: 8 December 2008

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2008.03.038

zbMATH Keywords

robustnessasymptotic relative efficiencybreakdown pointfunctional delta methodHadamard derivativeTukey depthmultivariate trimmed meantrimmed region

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Central limit and other weak theorems (60F05) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items

Unnamed Item ⋮ A note on weak convergence of general halfspace depth trimmed means ⋮ Halfspace depth and floating body ⋮ Discussion

Uses Software

• AS 307

Cites Work

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• Von Mises calculus for statistical functionals
• Asymptotics for the Tukey median
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• A differential for L-statistics
• Asymptotics for multivariate trimming
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• Multivariate analysis by data depth: Descriptive statistics, graphics and inference. (With discussions and rejoinder)
• Asymptotic distributions of the maximal depth estimators for regression and multivariate location
• Linear functions of order statistics with smooth weight functions
• General notions of statistical depth function.
• The influence function and maximum bias of Tukey's median
• Asymptotics for the Tukey depth process, with an application to a multivariate trimmed mean
• On the Stahel-Donoho estimator and depth-weighted means of multivariate data.
• Influence function and maximum bias of projection depth based estimators.
• Robustness of the half-space median
• Weak convergence and empirical processes. With applications to statistics
• On min-max majority and deepest points
• Approximation Theorems of Mathematical Statistics
• Uniform Central Limit Theorems
• Asymptotic Statistics
• Real Analysis and Probability
• Uniformity in weak convergence
• Robust Statistics
• The depth function of a population distribution.

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