Modelling high-dimensional data by mixtures of factor analyzers

  title={Modelling high-dimensional data by mixtures of factor analyzers},
  author={G. McLachlan and D. Peel and Richard Bean},
  journal={Comput. Stat. Data Anal.},
  • G. McLachlan, D. Peel, Richard Bean
  • Published 2003
  • Mathematics, Computer Science
  • Comput. Stat. Data Anal.
  • We focus on mixtures of factor analyzers from the perspective of a method for model-based density estimation from high-dimensional data, and hence for the clustering of such data. This approach enables a normal mixture model to be fitted to a sample of n data points of dimension p, where p is large relative to n. The number of free parameters is controlled through the dimension of the latent factor space. By working in this reduced space, it allows a model for each component-covariance matrix… CONTINUE READING
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