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MATHEMATICAL SCIENCES RESEARCH JOURNAL ISSN 1537-5978
This paper proposed a new generalization of bounded Continuous multivariate symmetric probability distributions. In this paper, we visualize a new generalization of Sam-Solai’s Multivariate additive Gammadistribution from the uni-variate two parameters Gamma distribution. Further, we find its Marginal, Multivariate Conditional distributions, Multivariate Generating functions, Multivariate survival, hazard functions and also discussed it’s special cases. The special cases includes the transformation of Sam-Solai’s Multivariate additive Gamma distribution into Multivariate Chi-square distribution, Multivariate Erlang distribution, Two parameter Multivariate Gamma distribution, Multivariate Inverse Gamma distribution, Multivariate log Gamma distribution and Multivariate Nagakami-m distribution. Moreover, it is found that the bivariate correlation between two Gamma random variables purely depends on the shape parameter and we simulated and established selected standard bivariate gamma correlation bounds from 900 different combinations of values for shape parameter.
