9,320 research outputs found
Model Selection for Gaussian Mixture Models
This paper is concerned with an important issue in finite mixture modelling,
the selection of the number of mixing components. We propose a new penalized
likelihood method for model selection of finite multivariate Gaussian mixture
models. The proposed method is shown to be statistically consistent in
determining of the number of components. A modified EM algorithm is developed
to simultaneously select the number of components and to estimate the mixing
weights, i.e. the mixing probabilities, and unknown parameters of Gaussian
distributions. Simulations and a real data analysis are presented to illustrate
the performance of the proposed method
- …