Robust estimation of the mean vector for high-dimensional data set using robust clustering

DOI10.1080/02664763.2014.999030OpenAlexW1976792930MaRDI QIDQ5130235

Hamid Reza Shahriari, Orod Ahmadi

Publication date: 4 November 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2014.999030

zbMATH Keywords

multivariate statistical analysisrobust estimatorrobust clusteringminimum volume ellipsoidS-estimatorG-means

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• robustbase

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Algorithms to compute \(CM\)- and \(S\)-estimates for regression
• On the relation between S-estimators and M-estimators of multivariate location and covariance
• Projection pursuit
• Asymptotic behaviour of S-estimates of multivariate location parameters and dispersion matrices
• The asymptotics of Rousseeuw's minimum volume ellipsoid estimator
• Robust m-estimators of multivariate location and scatter
• Robustness properties of \(S\)-estimators of multivariate location and shape in high dimension
• Alternative c-means clustering algorithms
• Least Median of Squares Regression
• Finding the Number of Clusters in a Dataset
• Fuzzy Cluster Analysis from the Viewpoint of Robust Statistics
• Robust Statistics
• Robust Statistics