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Matrix reshaping for statistics

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  • Loperfido, Nicola

Abstract

The reshaping of a block matrix vectorizes, transposes and stacks on top of each other the blocks of the matrix itself. This paper investigates the statistical applications of matrix reshaping to three-way data, partial traces and measures of multivariate shape.

Suggested Citation

  • Loperfido, Nicola, 2025. "Matrix reshaping for statistics," Statistics & Probability Letters, Elsevier, vol. 219(C).
    • Handle: RePEc:eee:stapro:v:219:y:2025:i:c:s016771522400316x
    DOI: 10.1016/j.spl.2024.110347
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    References listed on IDEAS

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    1. Henze, Norbert, 1997. "Limit laws for multivariate skewness in the sense of Móri, Rohatgi and Székely," Statistics & Probability Letters, Elsevier, vol. 33(3), pages 299-307, May.
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    3. Loperfido, Nicola, 2021. "Some theoretical properties of two kurtosis matrices, with application to invariant coordinate selection," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
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    5. Katarzyna Filipiak & Augustyn Markiewicz, 2017. "Universally optimal designs under mixed interference models with and without block effects," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(6), pages 789-804, November.
    6. Pauliina Ilmonen & Hannu Oja & Robert Serfling, 2012. "On Invariant Coordinate System (ICS) Functionals," International Statistical Review, International Statistical Institute, vol. 80(1), pages 93-110, April.
    7. Loperfido, Nicola, 2015. "Vector-valued skewness for model-based clustering," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 230-237.
    8. Kunert, Joachim & Martin, R. J., 2000. "On the determination of optimal designs for an interference model," Technical Reports 2000,17, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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