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Empirical spectral processes and their applications to time series analysis

Author

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  • Dahlhaus, Rainer

Abstract

This paper is concerned with the estimation of the spectral measure of a stationary process. Empirical spectral processes indexed by classes of functions are considered and an equicontinuity condition and a weak convergence result for the resulting spectral process are proved. Furthermore, some applications to time series analysis are given.

Suggested Citation

  • Dahlhaus, Rainer, 1988. "Empirical spectral processes and their applications to time series analysis," Stochastic Processes and their Applications, Elsevier, vol. 30(1), pages 69-83, November.
    • Handle: RePEc:eee:spapps:v:30:y:1988:i:1:p:69-83
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    Citations

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    Cited by:

    1. Can, S.U. & Mikosch, T. & Samorodnitsky, G., 2010. "Weak Convergence of the function-indexed integrated periodogram for infinite variance processes," Other publications TiSEM 3be90f1b-2f53-4987-b46e-c, Tilburg University, School of Economics and Management.
    2. Ruprecht Puchstein & Philip Preuß, 2016. "Testing for Stationarity in Multivariate Locally Stationary Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(1), pages 3-29, January.
    3. Kokoszka, Piotr & Mikosch, Thomas, 2000. "The periodogram at the Fourier frequencies," Stochastic Processes and their Applications, Elsevier, vol. 86(1), pages 49-79, March.
    4. Damek, Ewa & Mikosch, Thomas & Zhao, Yuwei & Zienkiewicz, Jacek, 2023. "Whittle estimation based on the extremal spectral density of a heavy-tailed random field," Stochastic Processes and their Applications, Elsevier, vol. 155(C), pages 232-267.
    5. Fasen-Hartmann, Vicky & Mayer, Celeste, 2023. "Empirical spectral processes for stationary state space models," Stochastic Processes and their Applications, Elsevier, vol. 155(C), pages 319-354.
    6. Vicky Fasen-Hartmann & Celeste Mayer, 2022. "Whittle estimation for continuous-time stationary state space models with finite second moments," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(2), pages 233-270, April.
    7. Philip Preuss & Ruprecht Puchstein & Holger Dette, 2015. "Detection of Multiple Structural Breaks in Multivariate Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(510), pages 654-668, June.
    8. Yuichi Goto & Tobias Kley & Ria Van Hecke & Stanislav Volgushev & Holger Dette & Marc Hallin, 2021. "The Integrated Copula Spectrum," Working Papers ECARES 2021-29, ULB -- Universite Libre de Bruxelles.
    9. Mikosch, Thomas & Zhao, Yuwei, 2015. "The integrated periodogram of a dependent extremal event sequence," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 3126-3169.
    10. Kokoszka, P. & Mikosch, T., 1997. "The integrated periodogram for long-memory processes with finite or infinite variance," Stochastic Processes and their Applications, Elsevier, vol. 66(1), pages 55-78, February.
    11. Takayuki Shiohama & Masanobu Taniguchi, 2001. "Sequential Estimation for a Functional of the Spectral Density of a Gaussian Stationary Process," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 142-158, March.
    12. Jean‐Marc Bardet & Paul Doukhan & José Rafael León, 2008. "Uniform limit theorems for the integrated periodogram of weakly dependent time series and their applications to Whittle's estimate," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 906-945, September.
    13. Mikosch, T. & Norvaisa, R., 1997. "Uniform convergence of the empirical spectral distribution function," Stochastic Processes and their Applications, Elsevier, vol. 70(1), pages 85-114, October.
    14. Polonik, Wolfgang, 1997. "Minimum volume sets and generalized quantile processes," Stochastic Processes and their Applications, Elsevier, vol. 69(1), pages 1-24, July.

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