IDEAS home Printed from https://ideas.repec.org/a/eee/spapps/v197y2026ics0304414926000633.html

Asymptotic distribution and subsampling in spectral analysis for spectrally correlated processes

Author

Listed:
  • Dudek, Anna E.
  • Majewski, Bartosz

Abstract

Spectrally correlated processes are harmonizable processes with spectral measures concentrated on a countable union of curves. Our study focuses on the spectral analysis of spectrally correlated processes, particularly in scenarios where these support curves take the form of lines with possible non-unit slopes. This subclass of spectrally correlated processes finds practical application, for example, in the problem of locating moving sources like aircraft, rockets, or other hostile jamming emitters emitting communication signals. Our research is focused on a frequency-smoothed periodogram along the support line as the spectral density function estimator. We derive its asymptotic distribution and based on that, we discuss the asymptotic properties of the introduced coherence estimator. Additionally, we formulate a consistent subsampling technique tailored for spectral analysis of spectrally correlated processes. We construct subsampling-based confidence intervals for spectral characteristics. Finally, we provide a numerical example illustrating a model relevant to applications in acoustics and communications.

Suggested Citation

  • Dudek, Anna E. & Majewski, Bartosz, 2026. "Asymptotic distribution and subsampling in spectral analysis for spectrally correlated processes," Stochastic Processes and their Applications, Elsevier, vol. 197(C).
  • Handle: RePEc:eee:spapps:v:197:y:2026:i:c:s0304414926000633
    DOI: 10.1016/j.spa.2026.104931
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304414926000633
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.spa.2026.104931?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Dehay, Dominique, 1994. "Spectral analysis of the covariance of the almost periodically correlated processes," Stochastic Processes and their Applications, Elsevier, vol. 50(2), pages 315-330, April.
    2. Anna E. Dudek & Jacek Leśkow & Efstathios Paparoditis & Dimitris N. Politis, 2014. "A Generalized Block Bootstrap For Seasonal Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(2), pages 89-114, March.
    3. Lei Shi & Shilpi Jain & Praveen Agarwal & Yousif Altayed & Shaher Momani, 2022. "Asymptotic Analysis About The Periodogram Of A General Class Of Time Series Models With Spectral Supportson Lines Not Parallel To The Main Diagonal," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 30(10), pages 1-17, December.
    4. A. R. Soltani & A. R. Nematollahi & M. R. Mahmoudi, 2019. "On the asymptotic distribution of the periodograms for the discrete time harmonizable simple processes," Statistical Inference for Stochastic Processes, Springer, vol. 22(2), pages 307-322, July.
    5. A. Dudek, 2015. "Circular block bootstrap for coefficients of autocovariance function of almost periodically correlated time series," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(3), pages 313-335, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Politis, Dimitris, 2016. "HEGY test under seasonal heterogeneity," University of California at San Diego, Economics Working Paper Series qt2q4054kf, Department of Economics, UC San Diego.
    2. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    3. Leprince, Julien & Schledorn, Amos & Guericke, Daniela & Dominkovic, Dominik Franjo & Madsen, Henrik & Zeiler, Wim, 2023. "Can occupant behaviors affect urban energy planning? Distributed stochastic optimization for energy communities," Applied Energy, Elsevier, vol. 348(C).
    4. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2026. "Is the diurnal pattern sufficient to explain intraday variation in volatility? A nonparametric assessment," Papers 2601.16613, arXiv.org.
    5. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org, revised Aug 2025.
    6. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2016. "Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach," CREATES Research Papers 2016-27, Department of Economics and Business Economics, Aarhus University.
    7. Averkamp, Roland, 1997. "Conditions for the completeness of the spectral domain of a harmonizable process," Stochastic Processes and their Applications, Elsevier, vol. 72(1), pages 1-9, December.
    8. Edward L Valachovic, 2024. "Periodically correlated time series and the Variable Bandpass Periodic Block Bootstrap," PLOS ONE, Public Library of Science, vol. 19(9), pages 1-16, September.
    9. Dzikowski, Daniel & Jentsch, Carsten, 2025. "Structural periodic vector autoregressions," Journal of Econometrics, Elsevier, vol. 252(PA).
    10. Łukasz Lenart, 2016. "Generalized Resampling Scheme With Application to Spectral Density Matrix in Almost Periodically Correlated Class of Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 369-404, May.
    11. Zou, Nan & Politis, Dimitris N., 2021. "Bootstrap seasonal unit root test under periodic variation," Econometrics and Statistics, Elsevier, vol. 19(C), pages 1-21.
    12. Edward Valachovic, 2025. "The Variable Multiple Bandpass Periodic Block Bootstrap for Time Series With Multiple Periodic Correlations," Journal of Probability and Statistics, John Wiley & Sons, vol. 2025(1).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:spapps:v:197:y:2026:i:c:s0304414926000633. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/505572/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.