Entropy 2012, 14(5), 865-879; doi:10.3390/e14050865

Entropic Approach to Multiscale Clustering Analysis

1,* email and 2email
Received: 20 February 2012; in revised form: 3 May 2012 / Accepted: 4 May 2012 / Published: 9 May 2012
(This article belongs to the Special Issue Concepts of Entropy and Their Applications)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: Recently, a novel method has been introduced to estimate the statistical significance of clustering in the direction distribution of objects. The method involves a multiscale procedure, based on the Kullback–Leibler divergence and the Gumbel statistics of extreme values, providing high discrimination power, even in presence of strong background isotropic contamination. It is shown that the method is: (i) semi-analytical, drastically reducing computation time; (ii) very sensitive to small, medium and large scale clustering; (iii) not biased against the null hypothesis. Applications to the physics of ultra-high energy cosmic rays, as a cosmological probe, are presented and discussed.
Keywords: Kullback–Leibler divergence; multiscale clustering; ultra-high energy cosmic rays; extreme value theory
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MDPI and ACS Style

De Domenico, M.; Insolia, A. Entropic Approach to Multiscale Clustering Analysis. Entropy 2012, 14, 865-879.

AMA Style

De Domenico M, Insolia A. Entropic Approach to Multiscale Clustering Analysis. Entropy. 2012; 14(5):865-879.

Chicago/Turabian Style

De Domenico, Manlio; Insolia, Antonio. 2012. "Entropic Approach to Multiscale Clustering Analysis." Entropy 14, no. 5: 865-879.

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