Stochastic Modelling on Mixture Distributions with Properties and Its Applications to the Analyzing Cancer Survival Data
Abstract
This paper introduces a novel two-parameter mixture model, the Mixture of Gamma and Erlang Distributions (MGED), which combines the properties of both the Gamma and Erlang distributions. The study derives key statistical properties of the MGED, including moments, order statistics, stochastic ordering, and entropy, and reliability measures. The unknown parameters of the MGED are estimated using the maximum likelihood method. To illustrate the effectiveness of the proposed model, a real cancer data set is analyzed. The results demonstrate that the MGED offers a superior goodness-of-fit and greater flexibility compared to other distributions.
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