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APPLICATIONS OF INFORMATION MEASURES FOR THE STUDY OF GAUSSIAN DISTRIBUTIONS

Finding the relationships between information measures and statistical constants leads to the applicability of information theory to the field of statistics. In the existing literature of information theory, there are many well known information theoretic measures, each with its own merits, limitations and areas of applications. In the present communication, we have developed new generalized parametric divergence measure and provided its applications along with the other parametric information theoretic measure to the field of Statistics by establishing the relationships of information contents with some statistical constants of Gaussian distribution.