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Kullback–Leibler Divergence Measure for Multivariate Skew-Normal Distributions
- Source :
- Entropy, Vol 14, Iss 9, Pp 1606-1626 (2012)
- Publication Year :
- 2012
- Publisher :
- MDPI AG, 2012.
-
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.
Details
- Language :
- English
- ISSN :
- 10994300
- Volume :
- 14
- Issue :
- 9
- Database :
- Directory of Open Access Journals
- Journal :
- Entropy
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.4398e8e5de3470e9330ab4cb6d20ef3
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/e14091606