Kullback–Leibler Divergence Measure for Multivariate Skew-Normal DistributionsReportar como inadecuado




Kullback–Leibler Divergence Measure for Multivariate Skew-Normal Distributions - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

1

División de Investigación Pesquera, Instituto de Fomento Pesquero, Almte, Manuel Blanco Encalada 839, Valparaíso, 2361827, Chile

2

Departamento de Estadística, Universidad de Valparaíso, Gran Bretaña 1111, Playa Ancha, Valparaíso, 2360102, Chile

3

Departamento de Estadística, Facultad de Matemáticas, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, Macul, Santiago, 7820436, Chile





*

Author to whom correspondence should be addressed.



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. View Full-Text

Keywords: skew-normal; cross-entropy; Kullback–Leibler divergence; Jeffreys divergence; earthquakes; nonparametric clustering skew-normal; cross-entropy; Kullback–Leibler divergence; Jeffreys divergence; earthquakes; nonparametric clustering





Autor: Javier E. Contreras-Reyes 1,2,* and Reinaldo B. Arellano-Valle 3

Fuente: http://mdpi.com/



DESCARGAR PDF




Documentos relacionados