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A modified Multifractal Detrended Fluctuation Analysis (MFDFA) approach for multifractal analysis of precipitation

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  • Morales Martínez, Jorge Luis
  • Segovia-Domínguez, Ignacio
  • Rodríguez, Israel Quiros
  • Horta-Rangel, Francisco Antonio
  • Sosa-Gómez, Guillermo

Abstract

Multifractal Detrended Fluctuation Analysis (MFDFA) is an efficient method to investigate the long-term correlations of the power law of non-stationary time series, in which the elimination of local trends usually depends upon a fixed-constant polynomial order. In this paper, we propose a flexible set of polynomial and trigonometric functions to better detect, and correctly model, hidden local trends in the time series at different scales. We introduce the Multifractal Detrended Fluctuation Analysis with Polynomial and Trigonometric functions (MFDFAPT) method via optimal model selection from an optimization framework. The performance of MFDFAPT is assessed with extensive numerical experiments based on the multifractal binomial cascade process, fractional Brownian movements, and fractional Gaussian noises. MFDFAPT shows better performance than MFDFA in the approximation of the Hurst index, and correctly determines the scalar behavior in stationary and non-stationary series. Additionally we apply MFDFAPT to detect and characterize the scalar properties of the daily precipitation time series in meteorological stations of Tabasco, México. Our results confirm previous indications that the general Hurst exponent depends on the physiographic characteristics of the study area, and that fractal dimension correctly characterizes the series of daily precipitations in tropical regions.

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  • Morales Martínez, Jorge Luis & Segovia-Domínguez, Ignacio & Rodríguez, Israel Quiros & Horta-Rangel, Francisco Antonio & Sosa-Gómez, Guillermo, 2021. "A modified Multifractal Detrended Fluctuation Analysis (MFDFA) approach for multifractal analysis of precipitation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
  • Handle: RePEc:eee:phsmap:v:565:y:2021:i:c:s0378437120309092
    DOI: 10.1016/j.physa.2020.125611
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    as
    1. Gulich, Damián & Zunino, Luciano, 2014. "A criterion for the determination of optimal scaling ranges in DFA and MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 17-30.
    2. Arneodo, A. & Bacry, E. & Muzy, J.F., 1995. "The thermodynamics of fractals revisited with wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 213(1), pages 232-275.
    3. Zoltan Eisler & Janos Kertesz, 2004. "Multifractal model of asset returns with leverage effect," Papers cond-mat/0403767, arXiv.org, revised May 2004.
    4. Kantelhardt, Jan W. & Rybski, Diego & Zschiegner, Stephan A. & Braun, Peter & Koscielny-Bunde, Eva & Livina, Valerie & Havlin, Shlomo & Bunde, Armin, 2003. "Multifractality of river runoff and precipitation: comparison of fluctuation analysis and wavelet methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(1), pages 240-245.
    5. Zhi-Gang Shao & Peter D. Ditlevsen, 2016. "Contrasting scaling properties of interglacial and glacial climates," Nature Communications, Nature, vol. 7(1), pages 1-8, April.
    6. Yu, Zu-Guo & Leung, Yee & Chen, Yongqin David & Zhang, Qiang & Anh, Vo & Zhou, Yu, 2014. "Multifractal analyses of daily rainfall time series in Pearl River basin of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 193-202.
    7. Livina, V. & Ashkenazy, Y. & Kizner, Z. & Strygin, V. & Bunde, A. & Havlin, S., 2003. "A stochastic model of river discharge fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 330(1), pages 283-290.
    8. Alexander Ly & Maarten Marsman & Eric†Jan Wagenmakers, 2018. "Analytic posteriors for Pearson's correlation coefficient," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(1), pages 4-13, February.
    9. Rodriguez, Eduardo & Carlos Echeverría, Juan & Alvarez-Ramirez, Jose, 2007. "Detrending fluctuation analysis based on high-pass filtering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 699-708.
    10. Qian, Xi-Yuan & Gu, Gao-Feng & Zhou, Wei-Xing, 2011. "Modified detrended fluctuation analysis based on empirical mode decomposition for the characterization of anti-persistent processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4388-4395.
    11. Xiaohui Yuan & Bin Ji & Hao Tian & Yuehua Huang, 2014. "Multiscaling Analysis of Monthly Runoff Series Using Improved MF-DFA Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 3891-3903, September.
    12. Breslin, M.C. & Belward, J.A., 1999. "Fractal dimensions for rainfall time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 48(4), pages 437-446.
    13. Pawe{l} O'swic{e}cimka & Stanis{l}aw Dro.zd.z & Marcin Forczek & Stanis{l}aw Jadach & Jaros{l}aw Kwapie'n, 2013. "Detrended Cross-Correlation Analysis Consistently Extended to Multifractality," Papers 1308.6148, arXiv.org, revised Feb 2014.
    14. Castro, Jorge J. & Cârsteanu, Alin A. & Flores, Claudia G., 2004. "Intensity–duration–area–frequency functions for precipitation in a multifractal framework," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 206-210.
    15. He, Ling-Yun & Chen, Shu-Peng, 2011. "Multifractal Detrended Cross-Correlation Analysis of agricultural futures markets," Chaos, Solitons & Fractals, Elsevier, vol. 44(6), pages 355-361.
    16. Rafal Rak & Pawel Zik{e}ba, 2015. "Multifractal Flexibly Detrended Fluctuation Analysis," Papers 1510.05115, arXiv.org.
    17. Gao-Feng Gu & Wei-Xing Zhou, 2010. "Detrending moving average algorithm for multifractals," Papers 1005.0877, arXiv.org, revised Jun 2010.
    18. 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.
    19. Rehman, Shafiqur, 2009. "Study of Saudi Arabian climatic conditions using Hurst exponent and climatic predictability index," Chaos, Solitons & Fractals, Elsevier, vol. 39(2), pages 499-509.
    20. 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.
    21. Rehman, S. & Siddiqi, A.H., 2009. "Wavelet based hurst exponent and fractal dimensional analysis of Saudi climatic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 40(3), pages 1081-1090.
    22. Eisler, Z. & Kertész, J., 2004. "Multifractal model of asset returns with leverage effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 603-622.
    23. Benoit B. Mandelbrot, 1972. "Statistical Methodology for Nonperiodic Cycles: From the Covariance To R/S Analysis," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 3, pages 259-290, National Bureau of Economic Research, Inc.
    24. Hajian, S. & Movahed, M. Sadegh, 2010. "Multifractal Detrended Cross-Correlation Analysis of sunspot numbers and river flow fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4942-4957.
    25. Fu-Chuen Chang & Lorens Imhof & Yi-Ying Sun, 2013. "Exact $$D$$ -optimal designs for first-order trigonometric regression models on a partial circle," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(6), pages 857-872, August.
    26. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    27. Erjia Ge & Yee Leung, 2013. "Detection of crossover time scales in multifractal detrended fluctuation analysis," Journal of Geographical Systems, Springer, vol. 15(2), pages 115-147, April.
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    2. Mendonça, Suzielli M. & Cabella, Brenno C.T. & Martinez, Alexandre S., 2024. "A Multifractal Detrended Fluctuation Analysis approach using generalized functions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
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    7. Sierra-Porta, D. & Domínguez-Monterroza, Andy-Rafael, 2022. "Linking cosmic ray intensities to cutoff rigidity through multifractal detrented fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

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