Abstract. The development of interrelationships between divergence measures and the known statistical constants provide the applications of information theory to the field of statistics. In the literature of information measures, there exist many divergence measures for discrete probability distributions whereas we need such divergence measures for continuous distributions to extend the scope of their applications. In the present communication, we have introduced divergence measures for continuous variate distributions and then proved that the divergence between the joint distribution density and the product of the marginal distribution densities is a function of the correlation coefficient which obviously implies that the divergence is also a measure of the similarity or of the dissimilarity.

Received: October 24, 2013

AMS Subject Classification: 94A15, 94A17

Key Words and Phrases: Gaussian distribution, divergence, Chi-square statistic, correlation coefficient

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DOI: 10.12732/ijpam.v91i2.7 How to cite this paper?
Source: International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2014
Volume: 91
Issue: 2

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