Comments on ``The power of monitoring: how to make the most of a contaminated multivariate sample

DOI10.1007/s10260-017-0415-xzbMath1428.62226OpenAlexW2771917385MaRDI QIDQ2324278

Carlos Matrán, Agustín Mayo-Iscar, Alfonso Gordaliza, Luis Angel García-Escudero

Publication date: 11 September 2019

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: http://uvadoc.uva.es/handle/10324/38325

zbMATH Keywords

robustnessclusteringmonitoring

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Nonparametric robustness (62G35) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Diagnostics, and linear inference and regression (62J20)

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Cites Work

• Exploring the number of groups in robust model-based clustering
• Robust fitting of mixtures using the trimmed likelihood estimator
• A general trimming approach to robust cluster analysis
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• Trimmed \(k\)-means: An attempt to robustify quantizers
• A reweighting approach to robust clustering
• The power of monitoring: how to make the most of a contaminated multivariate sample
• Finding the Number of Normal Groups in Model-Based Clustering via Constrained Likelihoods
• Robust Estimation in the Normal Mixture Model Based on Robust Clustering