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Activity Number: 491
Type: Contributed
Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
Sponsor: International Indian Statistical Association
Abstract #316692
Title: Copula Based Gaussian Kernel Dependency Measures
Author(s): Angshuman Roy*
Companies: Indian Statistical Institute, Kolkata
Keywords: Dependency measure ; Copula ; Non-parametric
Abstract:

In this paper, I presented a copula based method for measuring dependence between random variables. Modified Renyi axioms, stated by B. Schweizer and E. F. Wolff (1981), gives a reasonable set of desiderata for a measure of dependence for continuously distributed random variables. In this paper, I discussed about those Renyi axioms that are satisfied by this dependency measure. Also other properties of this measure have been studied. A sample estimate of the measure has been given. I also have shown some advantageous properties that the sample estimate satisfies.

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