IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v389y2010i24p5573-5580.html

Preservation of long range temporal correlations under extreme random dilution

Author

Listed:
  • Mirzayof, Dror
  • Ashkenazy, Yosef

Abstract

Many natural time series exhibit long range temporal correlations that may be characterized by power-law scaling exponents. However, in many cases, the time series have uneven time intervals due to, for example, missing data points, noisy data, and outliers. Here we study the effect of randomly missing data points on the power-law scaling exponents of time series that are long range temporally correlated. The Fourier transform and detrended fluctuation analysis (DFA) techniques are used for scaling exponent estimation. We find that even under extreme dilution of more than 50%, the value of the scaling exponent remains almost unaffected. Random dilution is also applied on heart interbeat interval time series. It is found that dilution of 70%–80% of the data points leads to a reduction of only 8% in the scaling exponent; it is also found that it is possible to discriminate between healthy and heart failure subjects even under extreme dilution of more than 90%.

Suggested Citation

  • Mirzayof, Dror & Ashkenazy, Yosef, 2010. "Preservation of long range temporal correlations under extreme random dilution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5573-5580.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:24:p:5573-5580
    DOI: 10.1016/j.physa.2010.08.035
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437110007387
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2010.08.035?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. Peter Huybers & William Curry, 2006. "Links between annual, Milankovitch and continuum temperature variability," Nature, Nature, vol. 441(7091), pages 329-332, May.
    2. Plamen Ch. Ivanov & Luís A. Nunes Amaral & Ary L. Goldberger & Shlomo Havlin & Michael G. Rosenblum & Zbigniew R. Struzik & H. Eugene Stanley, 1999. "Multifractality in human heartbeat dynamics," Nature, Nature, vol. 399(6735), pages 461-465, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gilney Figueira Zebende & Florêncio Mendes Oliveira Filho & Juan Alberto Leyva Cruz, 2017. "Auto-correlation in the motor/imaginary human EEG signals: A vision about the FDFA fluctuations," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-13, September.
    2. Filho, F.M. Oliveira & Ribeiro, F.F. & Cruz, J.A. Leyva & de Castro, A.P. Nunes & Zebende, G.F., 2023. "Statistical study of the EEG in motor tasks (real and imaginary)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).

    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. repec:plo:pone00:0105379 is not listed on IDEAS
    2. Vitanov, Nikolay K. & Sakai, Kenshi & Dimitrova, Zlatinka I., 2008. "SSA, PCA, TDPSC, ACFA: Useful combination of methods for analysis of short and nonstationary time series," Chaos, Solitons & Fractals, Elsevier, vol. 37(1), pages 187-202.
    3. Luis A. N. Amaral & P. Gopikrishnan & Kaushik Matia & Vasiliki Plerou & H. E. Stanley, 2001. "Application of statistical physics methods and conceptsto the study of science & technology systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 51(1), pages 9-36, April.
    4. Zhang, Yin & Li, Jin & Wang, Jun, 2017. "Exploring stability of entropy analysis for signal with different trends," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 60-67.
    5. Li, Jin & Chen, Chen & Yao, Qin & Zhang, Peng & Wang, Jun & Hu, Jing & Feng, Feilong, 2018. "The effect of circadian rhythm on the correlation and multifractality of heart rate signals during exercise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1207-1213.
    6. Stanley, H.Eugene, 2000. "Exotic statistical physics: Applications to biology, medicine, and economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(1), pages 1-17.
    7. Yao, Wenpo & Yao, Wenli & Wang, Jun, 2021. "A novel parameter for nonequilibrium analysis in reconstructed state spaces," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    8. Yuxin Zhao & Shuai Chang & Chang Liu, 2015. "Multifractal theory with its applications in data management," Annals of Operations Research, Springer, vol. 234(1), pages 133-150, November.
    9. Wu, Yue & Shang, Pengjian & Chen, Shijian, 2019. "Modified multifractal large deviation spectrum based on CID for financial market system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1331-1342.
    10. Jovanovic, Tijana & Mejía, Alfonso & Gall, Heather & Gironás, Jorge, 2016. "Effect of urbanization on the long-term persistence of streamflow records," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 208-221.
    11. Dudkowska, A. & Makowiec, D., 2004. "Sleep and wake phase of heart beat dynamics by artificial insymmetrised patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 174-180.
    12. Rodriguez, Eduardo & Echeverria, Juan C. & Alvarez-Ramirez, Jose, 2009. "Fractality in electrocardiographic waveforms for healthy subjects and patients with ventricular fibrillation," Chaos, Solitons & Fractals, Elsevier, vol. 39(3), pages 1046-1054.
    13. West, Bruce J. & Latka, Miroslaw & Glaubic-Latka, Marta & Latka, Dariusz, 2003. "Multifractality of cerebral blood flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 318(3), pages 453-460.
    14. Li, Jin & Hu, Jing & Zhang, Yinhong & Zhang, Xiaofeng, 2011. "Dynamical complexity changes during two forms of meditation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2381-2387.
    15. Rodriguez, Eduardo & Echeverria, Juan C. & Alvarez-Ramirez, Jose, 2007. "Detrended fluctuation analysis of heart intrabeat dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 429-438.
    16. Conlon, Thomas & Cotter, John & Gençay, Ramazan, 2018. "Long-run wavelet-based correlation for financial time series," European Journal of Operational Research, Elsevier, vol. 271(2), pages 676-696.
    17. Vitanov, Nikolay K. & Yankulova, Elka D., 2006. "Multifractal analysis of the long-range correlations in the cardiac dynamics of Drosophila melanogaster," Chaos, Solitons & Fractals, Elsevier, vol. 28(3), pages 768-775.
    18. Saeed Aligholi & Manoj Khandelwal, 2022. "Order of Intermittent Rock Fractured Surfaces," Sustainability, MDPI, vol. 15(1), pages 1-7, December.
    19. Xue Pan & Lei Hou & Mutua Stephen & Huijie Yang & Chenping Zhu, 2014. "Evaluation of Scaling Invariance Embedded in Short Time Series," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-27, December.
    20. Nagarajan, Radhakrishnan & Kavasseri, Rajesh G., 2005. "Minimizing the effect of trends on detrended fluctuation analysis of long-range correlated noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 182-198.
    21. Pawe{l} O'swik{e}cimka & Stanis{l}aw Dro.zd.z & Mattia Frasca & Robert Gk{e}barowski & Natsue Yoshimura & Luciano Zunino & Ludovico Minati, 2020. "Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses," Papers 2004.03319, arXiv.org.

    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:phsmap:v:389:y:2010:i:24:p:5573-5580. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.