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A mixture of SDB skew-t factor analyzers

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  • Murray, Paula M.
  • Browne, Ryan P.
  • McNicholas, Paul D.

Abstract

Mixtures of skew-t distributions offer a flexible choice for model-based clustering. A mixture model of this sort can be implemented using a variety of formulations of the skew-t distribution. A mixture of skew-t factor analyzers model for clustering of high-dimensional data using a flexible formulation of the skew-t distribution is developed. Methodological details of the proposed approach, which represents an extension of the mixture of factor analyzers model to a flexible skew-t distribution, are outlined and details of parameter estimation are provided. Clustering results are illustrated and compared to an alternative formulation of the mixture of skew-t factor analyzers model as well as the mixture of factor analyzers model.

Suggested Citation

  • Murray, Paula M. & Browne, Ryan P. & McNicholas, Paul D., 2017. "A mixture of SDB skew-t factor analyzers," Econometrics and Statistics, Elsevier, vol. 3(C), pages 160-168.
    • Handle: RePEc:eee:ecosta:v:3:y:2017:i:c:p:160-168
    DOI: 10.1016/j.ecosta.2017.05.001
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    References listed on IDEAS

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    9. Wan-Lun Wang & Tsung-I Lin, 2022. "Robust clustering of multiply censored data via mixtures of t factor analyzers," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 22-53, March.

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