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Study of cross-correlation in a self-affine time series of taxi accidents

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  • Zebende, G.F.
  • da Silva, P.A.
  • Machado Filho, A.

Abstract

We study in this paper the cross-correlation between self-affine time series of real variables recorded simultaneously in cases of taxi accidents. For this purpose, we apply the DCCA method and show that the cross-correlation can be divided into three distinct groups, if we look for the detrended covariance function, i.e., long-range cross-correlations, short-range cross-correlations and no cross-correlations. Finally, it will be seen that the detrended covariance function is robust, if compared with other methods, in identifying these types of cross-correlations.

Suggested Citation

  • Zebende, G.F. & da Silva, P.A. & Machado Filho, A., 2011. "Study of cross-correlation in a self-affine time series of taxi accidents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(9), pages 1677-1683.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:9:p:1677-1683
    DOI: 10.1016/j.physa.2010.12.038
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    Cited by:

    1. Li, Bao-Gen & Ling, Dian-Yi & Yu, Zu-Guo, 2021. "Multifractal temporally weighted detrended partial cross-correlation analysis of two non-stationary time series affected by common external factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    2. Delignières, Didier & Marmelat, Vivien, 2014. "Strong anticipation and long-range cross-correlation: Application of detrended cross-correlation analysis to human behavioral data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 47-60.
    3. Duncan A J Blythe & Vadim V Nikulin, 2017. "Long-range temporal correlations in neural narrowband time-series arise due to critical dynamics," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-28, May.
    4. Min, Seungsik & Shin, Ki-Hong & Baek, Woonhak & Kim, Kyungsik & You, Cheol-Hwan & Lee, Dong-In & Yum, Seong Soo & Kim, Wonheung & Chang, Ki-Ho, 2020. "Dynamical behavior of combined detrended cross-correlation analysis methods in random walks and Lévy flights," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    5. Wang, Dong-Hua & Suo, Yuan-Yuan & Yu, Xiao-Wen & Lei, Man, 2013. "Price–volume cross-correlation analysis of CSI300 index futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(5), pages 1172-1179.
    6. Di Sanzo, Silvestro, 2018. "A Markov switching long memory model of crude oil price return volatility," Energy Economics, Elsevier, vol. 74(C), pages 351-359.
    7. Zhuang, Xiaoyang & Wei, Yu & Ma, Feng, 2015. "Multifractality, efficiency analysis of Chinese stock market and its cross-correlation with WTI crude oil price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 101-113.
    8. da Silva Filho, A.M. & Zebende, G.F. & Guedes, E.F., 2021. "Analysis of intentional lethal violent crimes: A sliding windows approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    9. Santos, E.C.O. & Guedes, E.F. & Zebende, G.F. & da Silva Filho, A.M., 2022. "Autocorrelation of wind speed: A sliding window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    10. Khondekar, Mofazzal Hossain & Ghosh, Koushik & Bhattacharjee, Anup Kumar, 2016. "Scaling and nonlinear behaviour of daily mean temperature time series across IndiaAuthor-Name: Ray, Rajdeep," Chaos, Solitons & Fractals, Elsevier, vol. 84(C), pages 9-14.
    11. Zhang, Chen & Ni, Zhiwei & Ni, Liping, 2015. "Multifractal detrended cross-correlation analysis between PM2.5 and meteorological factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 114-123.
    12. Wei, Yu & Chen, Wang & Lin, Yu, 2013. "Measuring daily Value-at-Risk of SSEC index: A new approach based on multifractal analysis and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2163-2174.
    13. Sun, Xuelian & Liu, Zixian, 2016. "Optimal portfolio strategy with cross-correlation matrix composed by DCCA coefficients: Evidence from the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 667-679.
    14. Cao, Guangxi & Cao, Jie & Xu, Longbing & He, LingYun, 2014. "Detrended cross-correlation analysis approach for assessing asymmetric multifractal detrended cross-correlations and their application to the Chinese financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 460-469.
    15. Zebende, G.F. & Brito, A.A. & Castro, A.P., 2020. "DCCA cross-correlation analysis in time-series with removed parts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    16. Ferreira, Paulo & Kristoufek, Ladislav & Pereira, Eder Johnson de Area Leão, 2020. "DCCA and DMCA correlations of cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    17. Liu, Li & Ma, Guofeng, 2014. "Cross-correlation between crude oil and refined product prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 284-293.
    18. Ma, Feng & Wei, Yu & Huang, Dengshi, 2013. "Multifractal detrended cross-correlation analysis between the Chinese stock market and surrounding stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1659-1670.
    19. Machado Filho, A. & da Silva, M.F. & Zebende, G.F., 2014. "Autocorrelation and cross-correlation in time series of homicide and attempted homicide," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 12-19.
    20. da Silva, L.S. Almeida & Guedes, E.F. & Ferreira, Paulo & Dionísio, Andreia & Zebende, G.F., 2019. "ρx,y between open-close stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    21. Ferreira, Paulo & Quintino, Derick & Wundervald, Bruna & Dionísio, Andreia & Aslam, Faheem & Cantarinha, Ana, 2021. "Is Brazilian music getting more predictable? A statistical physics approach for different music genres," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).

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