Mahalanobis distance based on minimum regularized covariance determinant estimators for high dimensional data

DOI10.1080/03610926.2020.1719420OpenAlexW3003179961MaRDI QIDQ5078073

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Publication date: 20 May 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2020.1719420

zbMATH Keywords

high dimensional datarobust distancesMahalanobis distancesminimum diagonal product estimatorsminimum regularized covariance estimators

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

A robust Hotelling test statistic for one sample case in high dimensional data

Uses Software

• robustbase
• ROBPCA
• rrcov

Cites Work

• Unnamed Item
• The minimum regularized covariance determinant estimator
• Breakdown points of affine equivariant estimators of multivariate location and covariance matrices
• Influence function and efficiency of the minimum covariance determinant scatter matrix estimator
• Outlier detection for high-dimensional data
• Alternatives to the Median Absolute Deviation
• Three estimators of the Mahalanobis distance in high-dimensional data

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