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A central limit theorem for non-instantaneous filters of a stationary Gaussian process

Author

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  • Ho, Hwai-Chung
  • Sun, Tze-Chien

Abstract

A central limit theorem for a class of non-instantaneous filters of a stationary Gaussian process is proved and it is applied to study the limiting distributions of the number of zero-crossings.

Suggested Citation

  • Ho, Hwai-Chung & Sun, Tze-Chien, 1987. "A central limit theorem for non-instantaneous filters of a stationary Gaussian process," Journal of Multivariate Analysis, Elsevier, vol. 22(1), pages 144-155, June.
  • Handle: RePEc:eee:jmvana:v:22:y:1987:i:1:p:144-155
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    Citations

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    Cited by:

    1. Bai, Shuyang & Taqqu, Murad S. & Zhang, Ting, 2016. "A unified approach to self-normalized block sampling," Stochastic Processes and their Applications, Elsevier, vol. 126(8), pages 2465-2493.
    2. Ole E. Barndorff-Nielsen & José Manuel Corcuera & Mark Podolskij, 2009. "Multipower Variation for Brownian Semistationary Processes," CREATES Research Papers 2009-21, Department of Economics and Business Economics, Aarhus University.
    3. Alexeev, Vitali & Maynard, Alex, 2012. "Localized level crossing random walk test robust to the presence of structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3322-3344.
    4. Mynbayev, Kairat & Darkenbayeva, Gulsim, 2019. "Analyzing variance in central limit theorems," MPRA Paper 101685, University Library of Munich, Germany.
    5. Robinson, P. M., 2001. "The memory of stochastic volatility models," Journal of Econometrics, Elsevier, vol. 101(2), pages 195-218, April.
    6. Sánchez de Naranjo, M. V., 1995. "A central limit theorem for non-linear functionals of stationary Gaussian vector processes," Statistics & Probability Letters, Elsevier, vol. 22(3), pages 223-230, February.

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