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Kendall’s tau and agglomerative clustering for structure determination of hierarchical Archimedean copulas

Kendall’s tau and agglomerative clustering for structure determination of hierarchical... AbstractSeveral successful approaches to structure determination of hierarchical Archimedean copulas (HACs) proposed in the literature rely on agglomerative clustering and Kendall’s correlation coefficient. However, there has not been presented any theoretical proof justifying such approaches. This work fills this gap and introduces a theorem showing that, given the matrix of the pairwise Kendall correlation coefficients corresponding to a HAC, its structure can be recovered by an agglomerative clustering technique. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Dependence Modeling de Gruyter

Kendall’s tau and agglomerative clustering for structure determination of hierarchical Archimedean copulas

Dependence Modeling , Volume 5 (1): 13 – Jan 26, 2017

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Publisher
de Gruyter
Copyright
© 2017
ISSN
2300-2298
eISSN
2300-2298
DOI
10.1515/demo-2017-0005
Publisher site
See Article on Publisher Site

Abstract

AbstractSeveral successful approaches to structure determination of hierarchical Archimedean copulas (HACs) proposed in the literature rely on agglomerative clustering and Kendall’s correlation coefficient. However, there has not been presented any theoretical proof justifying such approaches. This work fills this gap and introduces a theorem showing that, given the matrix of the pairwise Kendall correlation coefficients corresponding to a HAC, its structure can be recovered by an agglomerative clustering technique.

Journal

Dependence Modelingde Gruyter

Published: Jan 26, 2017

References