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• W3104348521 abstract "Let there be given a contaminated list of n ℝd-valued observations coming from g different, normally distributed populations with a common covariance matrix. We compute the ML-estimator with respect to a certain statistical model with n−r outliers for the parameters of the g populations; it detects outliers and simultaneously partitions their complement into g clusters. It turns out that the estimator unites both the minimum-covariance-determinant rejection method and the well-known pooled determinant criterion of cluster analysis. We also propose an efficient algorithm for approximating this estimator and study its breakdown points for mean values and pooled SSP matrix." @default.
• W3104348521 created "2020-11-23" @default.
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• W3104348521 date "2005-02-01" @default.
• W3104348521 modified "2023-10-12" @default.
• W3104348521 title "A robust method for cluster analysis" @default.
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• W3104348521 doi "https://doi.org/10.1214/009053604000000940" @default.
• W3104348521 hasPublicationYear "2005" @default.
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