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

Górecki J. (), Hofert M. () and Holeňa M. ()
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Górecki J.: Department of Informatics, SBA in Karviná, Silesian University in Opava, Univerzitní námestí 1934/3, 733 40 Karviná, Czech Republic
Hofert M.: Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, ON, Canada
Holeňa M.: Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod vodárenskou veží 271/2, 182 07 Praha, Czech Republic

Dependence Modeling, 2017, vol. 5, issue 1, 75-87

Abstract: Several 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.

Keywords: structure determination; agglomerative clustering; Kendall’s tau; Archimedean copula (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:demode:v:5:y:2017:i:1:p:75-87:n:5

DOI: 10.1515/demo-2017-0005

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