Li, Guoying; Chen, Zhonglian Projection-pursuit approach to robust dispersion matrices and principal components: Primary theory and Monte Carlo. (English) Zbl 0595.62060 J. Am. Stat. Assoc. 80, 759-766 (1985). Robust estimators of covariance matrices and principal components based on the projection-pursuit technique are proposed. Rotational equivariance is proved. The level of the breakdown point is discussed. Qualitative robustness and consistency are shown for elliptic distributions. A Monte Carlo study illustrates the method and indicates that the method has a high breakdown point even for asymmetric contamination. Reviewer: J.Á.Višek Cited in 4 ReviewsCited in 56 Documents MSC: 62H99 Multivariate analysis 62F35 Robustness and adaptive procedures (parametric inference) 62H25 Factor analysis and principal components; correspondence analysis 62H12 Estimation in multivariate analysis Keywords:M-estimators; covariance matrix; principal components; projection-pursuit technique; Rotational equivariance; breakdown point; robustness; consistency; elliptic distributions; Monte Carlo study; asymmetric contamination PDFBibTeX XMLCite \textit{G. Li} and \textit{Z. Chen}, J. Am. Stat. Assoc. 80, 759--766 (1985; Zbl 0595.62060) Full Text: DOI