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Estimation Parameters of Mixture of Multivariate Normal Pattern

P. Nasiri, A. Aneshkani


In many application problems assessment are proper models for distribution of society’s quality is very important. Natural phenomenon usually has multivariate evidence that has influence on many argument and have heterogeneous. Application of mixture distributions has great background in medicine, agronomy, aerology, marketing, management and etc. Profit of this distribution when data set have outlier and missing data is very clear. We can consider Mixture distribution as a good modeling on many famous distributions such as Uniform, Normal, Poisson, Multinomial and etc. Aim of any statistical modeling is estimating parameters, for estimating parameters have various ways such as Moments approach, Maximum Likelihood, Monte Carlo, EM and MCMC algorithms. In this paper we consider multivariate normal mixture models.


Multivariate Normal Mixture Model, Identifiability, homoscedasticity, heteroscedasticity, likelihood function

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