A Simulation Study of a Parametric Mixture Model of Three Different Distributions to Analyze Heterogeneous Survival Data

Yusuf Mohammed, Bidin Yatim and Suzilah Ismail

Modern Applied Science, 2013, vol. 7, issue 7, 1

Abstract: In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data. Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated. The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters. The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme. The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model. The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.

Date: 2013
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