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Название: A Bayesian predictive approach to determining the number of components in a mixture distribution
Авторы: Dey D.K., Kuo L., Sahu S.K.
This paper describes a Bayesian approach to mixture modelling and a method based on predictive distribution to determine the number of components in the mixtures. The implementation is done through the use of the Gibbs sampler. The method is described through the mixtures of normal and gamma distributions. Analysis is presented in one simulated and one real data example. The Bayesian results are then compared with the likelihood approach for the two examples.