Sensitivity Coefficient in Principal Component Analysis: Robust Case

DOI10.1080/03610910802082467zbMath1151.62329OpenAlexW2091254264MaRDI QIDQ3543706

M. Ibazizen, Malika Cheikh

Publication date: 4 December 2008

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610910802082467

zbMATH Keywords

principal component analysisinfluence functionsensitivity coefficientreweighted minimum covariance determinant

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (1)

Comparative Study of Robust Estimators Based on a Sensitivity Coefficient in Principal Component Analysis

Cites Work

• High breakdown estimators for principal components: the projection-pursuit approach revis\-ited
• Breakdown points of affine equivariant estimators of multivariate location and covariance matrices
• Asymptotic behaviour of S-estimates of multivariate location parameters and dispersion matrices
• Robust m-estimators of multivariate location and scatter
• Asymptotics of reweighted estimators of multivariate location and scatter
• Influence function and efficiency of the minimum covariance determinant scatter matrix estimator
• Sensitivity analysis in principal component analysis:influence on the subspace spanned by principal components.
• Projection-Pursuit Approach to Robust Dispersion Matrices and Principal Components: Primary Theory and Monte Carlo
• Influence in principal components analysis
• Local influence in principal components analysis
• Principal component analysis based on robust estimators of the covariance or correlation matrix: influence functions and efficiencies

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