A Stochastic Modeling on Mixture Distribution with Application to Using Cancer Survival Data - Sakthivel, M.; Pandiyan, P. (Journal of Mathematics and Applied Statistics, 2024)
In this paper, specific statistical considerations are typically required, in order to select the best model for fitting survival data. The proposed the new mixture of Gamma and Shanker Distribution (MGSD), so named because it specifically mixes of two distributions: Shanker and gamma. There is also Reliability Analysis, statistical features such as stochastic ordering, moments, order statistics, entropy, and the Maximum Likelihood Estimation of the model parameters estimating. Lastly, a two real cancer data set is used to demonstrate the use of the AIC, BIC, and AICC model selection methods. It is compared with the fit and shows that the (MGS) distribution is more flexible than the other distributions.