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Contamination transformation matrix mixture modeling for skewed data groups with heavy tails and scatter

Author

Listed:
  • Xuwen Zhu

    (The University of Alabama)

  • Yana Melnykov

    (The University of Alabama)

  • Angelina S. Kolomoytseva

    (The University of Alabama)

Abstract

Model-based clustering is a popular application of the rapidly developing area of finite mixture modeling. While there is ample work focusing on clustering multivariate data, an increasing number of advancements have been aiming at the expansion of existing theory to the matrix-variate framework. Matrix-variate Gaussian mixtures are most popular in this setting despite the potential misfit for skewed and heavy-tailed data. To overcome this lack of flexibility, a new contaminated transformation matrix mixture model is proposed. We illustrate its utility in a series of experiments on simulated data and apply to a real-life data set containing COVID-related information. The performance of the developed model is promising in all considered settings.

Suggested Citation

  • Xuwen Zhu & Yana Melnykov & Angelina S. Kolomoytseva, 2024. "Contamination transformation matrix mixture modeling for skewed data groups with heavy tails and scatter," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 18(1), pages 85-101, March.
    • Handle: RePEc:spr:advdac:v:18:y:2024:i:1:d:10.1007_s11634-023-00550-w
    DOI: 10.1007/s11634-023-00550-w
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    References listed on IDEAS

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    1. Gallaugher, Michael P.B. & McNicholas, Paul D., 2019. "Three skewed matrix variate distributions," Statistics & Probability Letters, Elsevier, vol. 145(C), pages 103-109.
    2. Zhu, Xuwen & Melnykov, Volodymyr, 2018. "Manly transformation in finite mixture modeling," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 190-208.
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    7. Yana Melnykov & Xuwen Zhu & Volodymyr Melnykov, 2021. "Transformation mixture modeling for skewed data groups with heavy tails and scatter," Computational Statistics, Springer, vol. 36(1), pages 61-78, March.
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