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Title: A generalized spatial sign covariance matrix Authors:  Jakob Raymaekers - KULeuven (Belgium) [presenting]
Peter Rousseeuw - KU Leuven (Belgium)
Abstract: The well-known spatial sign covariance matrix (SSCM) carries out a radial transform which moves all data points to a sphere, followed by computing the classical covariance matrix of the transformed data. We study more general radial functions. It is shown that the eigenvectors of the generalized SSCM are still consistent. The breakdown value of the resulting scatter matrix is derived and the influence function is calculated. A simulation study indicates that the best results are obtained when the inner half of the data points are not transformed and points lying far away are moved toward the center.