IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v98y2015icp144-150.html
   My bibliography  Save this article

The difference of symmetric quantiles under long range dependence

Author

Listed:
  • Tarr, G.
  • Weber, N.C.
  • Müller, S.

Abstract

This paper investigates two robust estimators of the scale parameter given data from a stationary, long range dependent Gaussian process. In particular the limiting distributions of the interquartile range and related τ-quantile range statistics are established. In contrast to single quantiles, the limiting distribution of the difference of two symmetric quantiles is determined by the level of dependence in the underlying process. It is shown that there is no loss of asymptotic efficiency for the τ-quantile range relative to the standard deviation under extreme long range dependence which is consistent with results found previously for other estimators of scale.

Suggested Citation

  • Tarr, G. & Weber, N.C. & Müller, S., 2015. "The difference of symmetric quantiles under long range dependence," Statistics & Probability Letters, Elsevier, vol. 98(C), pages 144-150.
    • Handle: RePEc:eee:stapro:v:98:y:2015:i:c:p:144-150
    DOI: 10.1016/j.spl.2014.12.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S016771521400426X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2014.12.022?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Chan, Wai-sum, 1995. "Outliers and financial time series modelling: A cautionary note," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(3), pages 425-430.
    2. Garth Tarr & Samuel Müller & Neville Weber, 2012. "A robust scale estimator based on pairwise means," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(1), pages 187-199.
    3. Cheolwoo Park & F�lix Hernández-Campos & Long Le & J. S. Marron & Juhyun Park & Vladas Pipiras & F. D. Smith & Richard L. Smith & Michele Trovero & Zhengyuan Zhu, 2011. "Long-range dependence analysis of Internet traffic," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(7), pages 1407-1433, June.
    4. Wendler, Martin, 2011. "Bahadur representation for U-quantiles of dependent data," Journal of Multivariate Analysis, Elsevier, vol. 102(6), pages 1064-1079, July.
    5. Céline Lévy‐Leduc & Hélène Boistard & Eric Moulines & Murad S. Taqqu & Valderio A. Reisen, 2011. "Robust estimation of the scale and of the autocovariance function of Gaussian short‐ and long‐range dependent processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(2), pages 135-156, March.
    6. Wendler, Martin, 2012. "U-processes, U-quantile processes and generalized linear statistics of dependent data," Stochastic Processes and their Applications, Elsevier, vol. 122(3), pages 787-807.
    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. Reisen, Valdério Anselmo & Monte, Edson Zambon & da Conceição Franco, Glaura & Sgrancio, Adriano Marcio & Molinares, Fábio Alexander Fajardo & Bondon, Pascal & Ziegelmann, Flávio Augusto & Abraham, Bo, 2018. "Robust estimation of fractional seasonal processes: Modeling and forecasting daily average SO2 concentrations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 146(C), pages 27-43.
    2. Bhagaban Behera, 2013. "Drug Trafficking as a Non-Traditional Security Threat to Central Asian States," Jadavpur Journal of International Relations, , vol. 17(2), pages 229-251, December.
    3. Zacharias Psaradakis & Marián Vávra, 2022. "Using Triples to Assess Symmetry Under Weak Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1538-1551, October.
    4. Bigsten, Arne & Tengstam, Sven, 2015. "International Coordination and the Effectiveness of Aid," World Development, Elsevier, vol. 69(C), pages 75-85.
    5. Fajardo, Fabio Alexander, 2011. "Some Alternatives for Robust Estimation of the Spectrum in Stationary Processes," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 31(1), March.
    6. Su, Peng & Tarr, Garth & Muller, Samuel & Wang, Suojin, 2024. "CR-Lasso: Robust cellwise regularized sparse regression," Computational Statistics & Data Analysis, Elsevier, vol. 197(C).
    7. Li, Ming & Zhang, Peidong & Leng, Jianxing, 2016. "Improving autocorrelation regression for the Hurst parameter estimation of long-range dependent time series based on golden section search," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 189-199.
    8. Li, Ming & Zhao, Wei, 2013. "On bandlimitedness and lag-limitedness of fractional Gaussian noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 1955-1961.
    9. Sharipov, Olimjon Sh. & Wendler, Martin, 2013. "Normal limits, nonnormal limits, and the bootstrap for quantiles of dependent data," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1028-1035.
    10. Marcel Bräutigam & Marie Kratz, 2019. "Bivariate FCLT for the Sample Quantile and Measures of Dispersion for Augmented GARCH(p, q) processes," Working Papers hal-02176276, HAL.
    11. M. Angeles Carnero & Ana Pérez & Esther Ruiz, 2016. "Identification of asymmetric conditional heteroscedasticity in the presence of outliers," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(1), pages 179-201, March.
    12. Dehling, Herold & Fried, Roland, 2012. "Asymptotic distribution of two-sample empirical U-quantiles with applications to robust tests for shifts in location," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 124-140.
    13. Marcel, Bräutigam & Marie, Kratz, 2019. "Bivariate FCLT for the Sample Quantile and Measures of Dispersion for Augmented GARCH(p, q) processes," ESSEC Working Papers WP1909, ESSEC Research Center, ESSEC Business School.
    14. Sarnaglia, A.J.Q. & Reisen, V.A. & Lévy-Leduc, C., 2010. "Robust estimation of periodic autoregressive processes in the presence of additive outliers," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2168-2183, October.
    15. Wendler, Martin, 2012. "U-processes, U-quantile processes and generalized linear statistics of dependent data," Stochastic Processes and their Applications, Elsevier, vol. 122(3), pages 787-807.
    16. Gabriel Rodriguez & Dionisio Ramirez, 2014. "A Note on the Size of the ADF Test with Additive Outliers and Fractional Errors. A Reappraisal about the (Non)Stationarity of the Latin-American Inflation Series," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 37(73), pages 113-132.
    17. Reisen, Valdério Anselmo & Sgrancio, Adriano Marcio & Lévy-Leduc, Céline & Bondon, Pascal & Monte, Edson Zambon & Aranda Cotta, Higor Henrique & Ziegelmann, Flávio Augusto, 2019. "Robust factor modelling for high-dimensional time series: An application to air pollution data," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 842-852.
    18. Lin Fan & Peter W. Glynn & Markus Pelger, 2018. "Change-Point Testing for Risk Measures in Time Series," Papers 1809.02303, arXiv.org, revised Jul 2023.
    19. Gabriel Rodriguez, 2013. "A Comparative Note About Estimation of the Fractional Parameter under Additive Outliers," Documentos de Trabajo / Working Papers 2013-356, Departamento de Economía - Pontificia Universidad Católica del Perú.
    20. Song, Wanqing & Li, Ming & Li, Yuanyuan & Cattani, Carlo & Chi, Chi-Hung, 2019. "Fractional Brownian motion: Difference iterative forecasting models," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 347-355.

    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:stapro:v:98:y:2015:i:c:p:144-150. 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/622892/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.