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Large-Sample Approximations for Variance-Covariance Matrices of High-Dimensional Time Series

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  • Steland, Ansgar
  • von Sachs, Rainer

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  • Steland, Ansgar & von Sachs, Rainer, 2017. "Large-Sample Approximations for Variance-Covariance Matrices of High-Dimensional Time Series," LIDAM Reprints ISBA 2017015, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2017015
    Note: In : Bernoulli : a journal of mathematical statistics and probability, vol. 23, no. 4A, p. 2299-2329 (2017)
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    Cited by:

    1. Steland, Ansgar, 2020. "Testing and estimating change-points in the covariance matrix of a high-dimensional time series," Journal of Multivariate Analysis, Elsevier, vol. 177(C).
    2. Steland, Ansgar, 2024. "Flexible nonlinear inference and change-point testing of high-dimensional spectral density matrices," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    3. Steland, Ansgar & von Sachs, Rainer, 2018. "Asymptotics for high-dimensional covariance matrices and quadratic forms with applications to the trace functional and shrinkage," Stochastic Processes and their Applications, Elsevier, vol. 128(8), pages 2816-2855.
    4. Zdeněk Hlávka & Marie Hušková & Simos G. Meintanis, 2020. "Change-point methods for multivariate time-series: paired vectorial observations," Statistical Papers, Springer, vol. 61(4), pages 1351-1383, August.

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