COMPARISON OF TWO-COMPONENT MIXTURE DISTRIBUTION MODELS FOR HETEROGENEOUS SURVIVAL DATASETS: A REVIEW STUDY

Abstract

Heterogeneous survival data can have two different distributions before and after a certain timebecause many factors affect the life of the creatures or machines. For this purpose, we use a mixture of twoidentical (same kind of) distributions of Exponential, Gamma, Lognormal and Weibull and also all pairwisecombinations of these distributions. In addition to the previous studies, we propose the mixture of Log-normaldistribution with the Exponential, Gamma and Weibull distributions. Maximum likelihood estimations ofparameters of the mixture distribution models are obtained by using the EM (Expectation Maximization)algorithm. Model performances are compared using goodness of fit tests and Akaike’s information criterion(AIC). Results indicate that, mixtures of two non-identical (different kind of) distributions are as useful asmixtures of identical distributions