Abstract

The formulation of generalized class of distributions for modeling and analyzing data in diverse domains is of enormous practical significance. Captivated by the need for greater flexibility and relevance when modeling data in practice, academics in probability and distribution theory have proposed, studied and implemented novel techniques of generating new distributions from existing models. The XGamma distribution has serious shortfalls when it comes to applications in real world data set. This has attracted researchers to develop more generalized XGamma distributions to provide the desired outcomes in applications. The focus of this curated compilation constitute freshly conceived illuminating extensions, generalizations and modifications of the XGamma distribution. This is expected to serve as a vibrant platform and future research direction for researchers in probability and distribution theory.    

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