An algorithm for estimating number of components of Gaussian mixture model based on penalized distance

@article{Zhang2008AnAF,
  title={An algorithm for estimating number of components of Gaussian mixture model based on penalized distance},
  author={DaMing Zhang and Hui Guo and Bin Luo},
  journal={2008 International Conference on Neural Networks and Signal Processing},
  year={2008},
  pages={482-487}
}
The expectation-maximization (EM) algorithm is a popular approach for parameter estimation of finite mixture model (FMM). A drawback of this approach is that the number of components of the finite mixture model is not known in advance, nevertheless, it is a key issue for EM algorithms. In this paper, a penalized minimum matching distance-guided EM algorithm is discussed. Under the framework of Greedy EM, a fast and accurate algorithm for estimating the number of components of the Gaussian… CONTINUE READING