Some theoretical properties of two kurtosis matrices, with application to invariant coordinate selection
Nicola Loperfido
Journal of Multivariate Analysis, 2021, vol. 186, issue C
Abstract:
Invariant coordinate selection (ICS) is a multivariate statistical method aimed at detecting data structures by means of the simultaneous diagonalization of two scatter matrices. Statistical applications of ICS include cluster analysis, independent component analysis, outlier detection, regression analysis and projection pursuit. Scatter matrices based on fourth-order moments often appear in ICS, partly due to their known asymptotic behaviour. This paper focuses on their theoretical properties, with special emphasis on symmetric distributions, finite mixtures and stochastic processes. Theoretical results highlight both appealing properties and limitations of kurtosis-based ICS as a tool for detecting data structures.
Keywords: Exchangeability; Kurtosis; Mixtures; Reversibility; Symmetry (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047259X21000877
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:186:y:2021:i:c:s0047259x21000877
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.jmva.2021.104809
Access Statistics for this article
Journal of Multivariate Analysis is currently edited by de Leeuw, J.
More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().