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Entropic Approach to Multiscale Clustering Analysis
School of Computer Science, University of Birmingham, Edgbaston B15 2TT Birmingham, UK
Dipartimento di Fisica e Astronomia, Universitá di Catania and INFN, Via S. Sofia 64, 95123 Catania, Italy
* Author to whom correspondence should be addressed.
Received: 20 February 2012; in revised form: 3 May 2012 / Accepted: 4 May 2012 / Published: 9 May 2012
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.
De Domenico M, Insolia A. Entropic Approach to Multiscale Clustering Analysis. Entropy. 2012; 14(5):865-879.
De Domenico, Manlio; Insolia, Antonio. 2012. "Entropic Approach to Multiscale Clustering Analysis." Entropy 14, no. 5: 865-879.