A New Mixture of Gamma Shape Distributions: Properties and Applications

Over the last few decades, mixture distributions are used in creating population from two or more distributions. Mixture distributions are a good application in the applications of medical science, biology, engineering, finance and economics. Gaussian mixture models have broad utility, including their usage for model-based clustering framework. Recently, there are indications to use of non-Gaussian mixture distributions to skewed and asymmetric data. We propose a mixture model of inverse power Gamma shape distributions (MIPGSD) to analyze positive data. Basic structural properties such raw and central moments and hazard rate function are obtained. Different estimation methods are studied to estimate the proposed model parameters. Simulation studies is done to present the performance and behavior of the different estimates of the proposed model parameters. A real data set is provided to compare the reliability of the new model with other models