A Stochastic Model of Mixture Distribution Properties and its Applications

Abstract

In this paper, specific statistical considerations are typically required in order to select the best model for fitting survival data. The new Mixture of Gompertz and Gamma Distribution (MGGD), which gets its name from the particular mixing of two distributions, Gompertz and Gamma, is proposed in this study. Also, the reliability analysis, statistical properties like stochastic ordering, moments, order statistics, and the estimation of parameters using the method of maximum likelihood estimation. Finally, an application of the goodness-of-fit criteria to a real cancer data set is shown. It is contrasted with the fit and demonstrates that the mixture of the Gompertz and gamma distributions has greater flexibility than the other distributions.