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Testing Independence via Spectral Moments

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Book cover Applied and Computational Matrix Analysis (MAT-TRIAD 2015)

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Abstract

Assume that a matrix \(X:p\times n\) is matrix normally distributed and that the Kolmogorov condition , i.e., \(\lim _{n,p\rightarrow \infty }\frac{n}{p}=c>0\), holds. We propose a test for identity of the covariance matrix using a goodness-of-fit approach. Calculations are based on a recursive formula derived by Pielaszkiewicz et al. [19]. The test performs well regarding the power compared to presented alternatives, for both \(c<1\) or \(c\ge 1\).

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Authors and Affiliations

  1. Linköping University, Linköping, Sweden

    Jolanta Pielaszkiewicz, Dietrich von Rosen & Martin Singull

  2. Linnaeus University, Växjö, Sweden

    Jolanta Pielaszkiewicz

  3. Swedish University of Agricultural Sciences, Uppsala, Sweden

    Dietrich von Rosen

Authors
  1. Jolanta Pielaszkiewicz
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  2. Dietrich von Rosen
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  3. Martin Singull
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Corresponding author

Correspondence to Jolanta Pielaszkiewicz .

Editor information

Editors and Affiliations

  1. Department of Mathematics, University of Coimbra, Coimbra, Portugal

    Natália Bebiano

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Pielaszkiewicz, J., von Rosen, D., Singull, M. (2017). Testing Independence via Spectral Moments. In: Bebiano, N. (eds) Applied and Computational Matrix Analysis. MAT-TRIAD 2015. Springer Proceedings in Mathematics & Statistics, vol 192. Springer, Cham. https://doi.org/10.1007/978-3-319-49984-0_18

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