A robust biplot

DOI10.2307/3315312zbMath0756.62001OpenAlexW2094859459MaRDI QIDQ4024618

Louis-Paul Rivest, Gaétan Daigle

Publication date: 4 February 1993

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

Full work available at URL: https://doi.org/10.2307/3315312

zbMATH Keywords

outliersleast-squaressingular-value decompositionscatter matrixlocation vectorHuber estimatorsrobust variance-covariance matrixmultivariate \(M\)-estimatesprocrustree rotationsrobust \(M\)- estimatesrobust biplotrobust correlationrobust principal- component analysisrobust standard deviation

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Robustness and adaptive procedures (parametric inference) (62F35) Graphical methods in statistics (62A09)

Related Items

Transposition invariant principal component analysis in \(L_{1}\) for long tailed data ⋮ Robust Q-mode principal component analysis in \(L_{1}\) ⋮ Robust centroid method ⋮ h‐plots for displaying nonmetric dissimilarity matrices

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Robust m-estimators of multivariate location and scatter
• Influence in principal components analysis
• Some Results on the Existence, Uniqueness, and Computation of the M-Estimates of Multivariate Location and Scatter
• Lower Rank Approximation of Matrices by Least Squares with Any Choice of Weights
• Robust Procedures in Multivariate Analysis I: Robust Covariance Estimation
• Graphical Exploration in Comparing Variance Matrices
• Some distance properties of latent root and vector methods used in multivariate analysis
• The biplot graphic display of matrices with application to principal component analysis

This page was built for publication: A robust biplot