Robust Detection of Multiple Outliers in Grouped Multivariate Data

DOI10.1080/02664760701592877OpenAlexW1988440675MaRDI QIDQ5123362

Nedret Billor, Chrys Caroni

Publication date: 28 September 2020

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

Full work available at URL: https://doi.org/10.1080/02664760701592877

zbMATH Keywords

outlierscluster analysismultivariate datarobust methodsBACON

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Detecting outliers and influential points: an indirect classical Mahalanobis distance-based method

Uses Software

• R
• S-PLUS
• ROBPCA
• clusfind
• mvBACON

Cites Work

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• Outlier detection in the multiple cluster setting using the minimum covariance determinant estimator
• BACON: blocked adaptive computationally efficient outlier nominators.
• Robust Procedures in Multivariate Analysis I: Robust Covariance Estimation
• Finding Groups in Data
• Identification of Outliers in Multivariate Data
• Wilks' outlier test in more than one multivariate sample
• Outlier detection by robust principal components analysis
• Sequential Application of Wilks's Multivariate Outlier Test

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