Mixtures of Factor Analyzers with Common Factor Loadings for the Clustering and Visualisation of High-Dimensional Data

@inproceedings{Baek2008MixturesOF,
  title={Mixtures of Factor Analyzers with Common Factor Loadings for the Clustering and Visualisation of High-Dimensional Data},
  author={Jangsun Baek and Geoffrey J. McLachlan},
  year={2008}
}
Mixtures of factor analyzers enable model-based density estimation and clustering to be undertaken for high-dimensional data, where the number of observations n is very large relative to their dimension p. In practice, there is often the need to reduce further the number of parameters in the specification of the componentcovariance matrices. To this end, we propose the use of common component-factor loadings, which considerably reduces further the number of parameters. Moreover, it allows the… CONTINUE READING
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