The use of a common location measure in the invariant coordinate selection and projection pursuit

Fatimah Alashwali and John T. Kent

Journal of Multivariate Analysis, 2016, vol. 152, issue C, 145-161

Abstract: Invariant coordinate selection (ICS) and projection pursuit (PP) are two methods that can be used to detect clustering directions in multivariate data by optimizing criteria sensitive to non-normality. In particular, ICS finds clustering directions using a relative eigen-decomposition of two scatter matrices with different levels of robustness; PP is a one-dimensional variant of ICS. Each of the two scatter matrices includes an implicit or explicit choice of location. However, when different measures of location are used, ICS and PP can behave counter-intuitively. In this paper we explore this behavior in a variety of examples and propose a simple and natural solution: use the same measure of location for both scatter matrices.

Keywords: Cluster analysis; Invariant coordinate selection; Projection pursuit; Robust scatter matrices; Location measures; Multivariate mixture model (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (7)

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DOI: 10.1016/j.jmva.2016.08.007

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