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Testing for subsphericity when n and p are of different asymptotic order

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  • Virta, Joni

Abstract

We extend a test of subsphericity to the high-dimensional Gaussian regime where the spikes diverge to infinity and p/n→{0,∞}. The test is used to derive a consistent estimator for the latent dimension of the model.

Suggested Citation

  • Virta, Joni, 2021. "Testing for subsphericity when n and p are of different asymptotic order," Statistics & Probability Letters, Elsevier, vol. 179(C).
    • Handle: RePEc:eee:stapro:v:179:y:2021:i:c:s0167715221001711
    DOI: 10.1016/j.spl.2021.109209
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    References listed on IDEAS

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    1. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
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    3. Schott, James R., 2006. "A high-dimensional test for the equality of the smallest eigenvalues of a covariance matrix," Journal of Multivariate Analysis, Elsevier, vol. 97(4), pages 827-843, April.
    4. Ningning Xia & Zhidong Bai, 2015. "Functional CLT of eigenvectors for large sample covariance matrices," Statistical Papers, Springer, vol. 56(1), pages 23-60, February.
    5. Wei Luo & Bing Li, 2016. "Combining eigenvalues and variation of eigenvectors for order determination," Biometrika, Biometrika Trust, vol. 103(4), pages 875-887.
    6. Birke, Melanie & Dette, Holger, 2005. "A note on testing the covariance matrix for large dimension," Statistics & Probability Letters, Elsevier, vol. 74(3), pages 281-289, October.
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    Cited by:

    1. Bernard, Gaspard & Verdebout, Thomas, 2024. "On testing the equality of latent roots of scatter matrices under ellipticity," Journal of Multivariate Analysis, Elsevier, vol. 199(C).

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