Extension of the mixture of factor analyzers model to incorporate the multivariate t-distribution

@article{McLachlan2007ExtensionOT,
  title={Extension of the mixture of factor analyzers model to incorporate the multivariate t-distribution},
  author={G. McLachlan and Richard Bean and L. B. Jones},
  journal={Comput. Stat. Data Anal.},
  year={2007},
  volume={51},
  pages={5327-5338}
}
  • G. McLachlan, Richard Bean, L. B. Jones
  • Published 2007
  • Mathematics, Computer Science
  • Comput. Stat. Data Anal.
  • Mixtures of factor analyzers enable model-based density estimation to be undertaken for high-dimensional data, where the number of observations n is small relative to their dimension p. However, this approach is sensitive to outliers as it is based on a mixture model in which the multivariate normal family of distributions is assumed for the component error and factor distributions. An extension to mixtures of t-factor analyzers is considered, whereby the multivariate t-family is adopted for… CONTINUE READING
    126 Citations

    Topics from this paper

    Mixtures of common t-factor analyzers for clustering high-dimensional microarray data
    • 67
    • PDF
    Extending mixtures of multivariate t-factor analyzers
    • 98
    • Highly Influenced
    • PDF
    4 Choice of Starting Values for the EM Algorithm
    • PDF
    Clustering of High-Dimensional and Correlated Data
    • 4
    • PDF
    Mixtures of Common Skew-t Factor Analyzers
    • 32
    • PDF
    Issues of robustness and high dimensionality in cluster analysis
    • 1
    Mixtures of skew-t factor analyzers
    • 79
    • PDF

    References

    SHOWING 1-10 OF 31 REFERENCES
    Modelling high-dimensional data by mixtures of factor analyzers
    • 235
    • PDF
    Robust mixture modelling using the t distribution
    • 722
    • PDF
    Robust Cluster Analysis via Mixtures of Multivariate t-Distributions
    • 166
    • PDF
    Mixtures of Factor Analysers. Bayesian Estimation and Inference by Stochastic Simulation
    • 64
    • PDF
    Robust Bayesian Mixture Modelling
    • 217
    • PDF
    Model-based Gaussian and non-Gaussian clustering
    • 2,097
    • PDF
    Mixtures of Probabilistic Principal Component Analyzers
    • 1,654
    • PDF