Kullback-Leibler divergence measure for multivariate skew-normal distributions

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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. © 2012 by the authors.

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Contreras-Reyes, J. E., & Arellano-Valle, R. B. (2012). Kullback-Leibler divergence measure for multivariate skew-normal distributions. Entropy, 14(9), 1606–1626. https://doi.org/10.3390/e14091606

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