Entropic Approach to Multiscale Clustering Analysis

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 discriminatio...

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Main Authors:	Antonio Insolia, Manlio De Domenico
Format:	Article
Language:	English
Published:	MDPI AG 2012-05-01
Series:	Entropy
Subjects:	Kullback–Leibler divergence multiscale clustering ultra-high energy cosmic rays extreme value theory
Online Access:	http://www.mdpi.com/1099-4300/14/5/865

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spelling	doaj-5faf6ca766d94e2f860d21dd58f6b0422020-11-24T23:18:37ZengMDPI AGEntropy1099-43002012-05-0114586587910.3390/e14050865Entropic Approach to Multiscale Clustering AnalysisAntonio InsoliaManlio De DomenicoRecently, 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.http://www.mdpi.com/1099-4300/14/5/865Kullback–Leibler divergencemultiscale clusteringultra-high energy cosmic raysextreme value theory
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Antonio Insolia Manlio De Domenico
spellingShingle	Antonio Insolia Manlio De Domenico Entropic Approach to Multiscale Clustering Analysis Entropy Kullback–Leibler divergence multiscale clustering ultra-high energy cosmic rays extreme value theory
author_facet	Antonio Insolia Manlio De Domenico
author_sort	Antonio Insolia
title	Entropic Approach to Multiscale Clustering Analysis
title_short	Entropic Approach to Multiscale Clustering Analysis
title_full	Entropic Approach to Multiscale Clustering Analysis
title_fullStr	Entropic Approach to Multiscale Clustering Analysis
title_full_unstemmed	Entropic Approach to Multiscale Clustering Analysis
title_sort	entropic approach to multiscale clustering analysis
publisher	MDPI AG
series	Entropy
issn	1099-4300
publishDate	2012-05-01
description	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.
topic	Kullback–Leibler divergence multiscale clustering ultra-high energy cosmic rays extreme value theory
url	http://www.mdpi.com/1099-4300/14/5/865
work_keys_str_mv	AT antonioinsolia entropicapproachtomultiscaleclusteringanalysis AT manliodedomenico entropicapproachtomultiscaleclusteringanalysis
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Entropic Approach to Multiscale Clustering Analysis

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