A simulation study of a parametric mixture model with three different distributions is considered in this paper to model heterogeneous survival data. The proposed parametric mixture of Exponential, Gamma, and Weibull has some properties that are investigated. To estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters, the Expectation Maximization Algorithm (EM) is used. The simulations are carried out by simulating data sampled from a population of three component parametric mixtures of three different distributions, and they are repeated 10, 30, 50, 100, and 500 times to investigate the effects. The EM scheme's consistency and stability The developed EM Algorithm scheme can estimate mixture parameters that are very close to the parameters of the postulated model. As the number of simulation repetitions increases, the parameters get closer and closer to the postulated models, with relatively small standard errors. The results showed that the EM estimated the parameters of the three component mixture model correctly.
Author(s) DetailsYusuf Abbakar MohammedI
Deptartment of Mathematical Sciences, Faculty of Sciences, University of Maiduguri, Nigeria.
Bidin Yatim
School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, Malaysia.
Suzilah Ismail
School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, Malaysia.
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