Estimating Parameters in Muitivariate Normal Mixtures Ahn, Sung-Mahn; Baik, Sung-Wook;
This paper investigates a penalized likelihood method for estimating the parameter of normal mixtures in multivariate settings with full covariance matrices. The proposed model estimates the number of components through the addition of a penalty term to the usual likelihood function and the construction of a penalized likelihood function. We prove the consistency of the estimator and present the simulation results on the multi-dimensional nor-mal mixtures up to the 8-dimension.
Multivariate normal mixtures;penalized likelihood;consistency of estimator;
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