Abstract
The development of interrelationships between divergence mea- sures 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.
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