Kullback-Leibler divergence measure for multivariate skew-normal distributions

Javier E. Contreras-Reyes, Reinaldo B. Arellano-Valle

Research output: Contribution to journalArticlepeer-review

72 Scopus citations

Abstract

The aim of this work is to provide the tools to compute the well-known Kullback-Leibler divergence measure for the flexible family of multivariate skew-normal distributions. In particular, we use the Jeffreys divergence measure to compare the multivariate normal distribution with the skew-multivariate normal distribution, showing that this is equivalent to comparing univariate versions of these distributions. Finally, we applied our results on a seismological catalogue data set related to the 2010 Maule earthquake. Specifically, we compare the distributions of the local magnitudes of the regions formed by the aftershocks.

Original languageEnglish
Pages (from-to)1606-1626
Number of pages21
JournalEntropy
Volume14
Issue number9
DOIs
StatePublished - Sep 2012
Externally publishedYes

Keywords

  • Cross-entropy
  • Earthquakes
  • Jeffreys divergence
  • Kullback-Leibler divergence
  • Nonparametric clustering
  • Skew-normal

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