A central limit theorem for multivariate generalized trimmed \(k\)-means

DOI10.1214/aos/1018031268zbMath0984.62042OpenAlexW1911405936MaRDI QIDQ1568311

Carlos Matrán, Alfonso Gordaliza, Luis Angel García-Escudero

Publication date: 13 May 2002

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1018031268

zbMATH Keywords

robustnessclusteringcentral limit theoremk-meansimpartial trimmingtolerance zones

Mathematics Subject Classification ID

Nonparametric robustness (62G35) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Central limit and other weak theorems (60F05) Nonparametric tolerance and confidence regions (62G15)

Related Items (11)

Strong Consistency of ReducedK-means Clustering ⋮ Fast and robust estimation of the multivariate errors in variables model ⋮ OWA-based robust fuzzy clustering of time series with typicality degrees ⋮ Central limit theorem and influence function for the MCD estimators at general multivariate distributions ⋮ Asymptotics of a clustering criterion for smooth distributions ⋮ Wide consensus aggregation in the Wasserstein space. Application to location-scatter families ⋮ A review of robust clustering methods ⋮ A general trimming approach to robust cluster analysis ⋮ On the asymptotics of trimmed best \(k\)-nets ⋮ A Robust Maximal F-Ratio Statistic to Detect Clusters Structure ⋮ Asymptotics of the empirical cross-over function

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