Alashwali, F and Kent, JT orcid.org/0000-0002-1861-8349 (2016) The use of a common location measure in the invariant coordinate selection and projection pursuit. Journal of Multivariate Analysis, 152. pp. 145-161. ISSN 0047-259X
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016, Elsevier. This is an author produced version of a paper published in l of Multivariate Analysis. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Cluster analysis; Invariant coordinate selection; Projection pursuit; Robust scatter matrices; Location measures; Multivariate mixture model |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 01 Sep 2016 11:40 |
Last Modified: | 31 Aug 2017 09:19 |
Published Version: | http://dx.doi.org/10.1016/j.jmva.2016.08.007 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.jmva.2016.08.007 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:104150 |