Principal Points and Self-Consistent Points of Symmetrical Multivariate Distributions

T. Tarpey

Journal of Multivariate Analysis, 1995, vol. 53, issue 1, 39-51

Abstract: The k principal points [xi]1, ..., [xi]k of a random vector X are the points that approximate the distribution of X by minimizing the expected squared distance of X to the nearest of the [xi]j. A given set of k points y1, ..., yk partition p into domains of attraction D1, ..., Dk respectively, where Dj,consists of all points x [set membership, variant] p such that [short parallel]x - yj[short parallel]

Date: 1995
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