Multifractal detrended fluctuation analysis of nonstationary time series Export

@article{citeulike:1199018, abstract = {We develop a method for the multifractal characterization of nonstationary time series, which is based on a generalization of the detrended fluctuation analysis (DFA). We relate our multifractal DFA method to the standard partition function-based multifractal formalism, and prove that both approaches are equivalent for stationary signals with compact support. By analyzing several examples we show that the new method can reliably determine the multifractal scaling behavior of time series. By comparing the multifractal DFA results for original series to those for shuffled series we can distinguish multifractality due to long-range correlations from multifractality due to a broad probability density function. We also compare our results with the wavelet transform modulus maxima (WTMM) method, and show that the results are equivalent.}, archivePrefix = {arXiv}, author = {Kantelhardt, Jan W. and Zschiegner, Stephan A. and Koscielny-Bunde, Eva and Bunde, Armin and Havlin, Shlomo and Stanley, H. Eugene}, citeulike-article-id = {1199018}, citeulike-linkout-0 = {http://arxiv.org/abs/physics/0202070}, citeulike-linkout-1 = {http://arxiv.org/pdf/physics/0202070}, citeulike-linkout-2 = {http://adsabs.harvard.edu/cgi-bin/nph-bib_query?bibcode=2002PhyA..316...87K}, day = {27}, eprint = {physics/0202070}, keywords = {detrended-fluctuation-analysis, long-range-correlation, multifractality, scaling, time-series-analysis}, month = {Feb}, posted-at = {2007-03-30 23:25:21}, priority = {2}, title = {Multifractal detrended fluctuation analysis of nonstationary time series}, url = {http://arxiv.org/abs/physics/0202070}, year = {2002} }

TY - JOUR ID - citeulike:1199018 L3 - citeulike-article-id:1199018 N2 - We develop a method for the multifractal characterization of nonstationary time series, which is based on a generalization of the detrended fluctuation analysis (DFA). We relate our multifractal DFA method to the standard partition function-based multifractal formalism, and prove that both approaches are equivalent for stationary signals with compact support. By analyzing several examples we show that the new method can reliably determine the multifractal scaling behavior of time series. By comparing the multifractal DFA results for original series to those for shuffled series we can distinguish multifractality due to long-range correlations from multifractality due to a broad probability density function. We also compare our results with the wavelet transform modulus maxima (WTMM) method, and show that the results are equivalent. TI - Multifractal detrended fluctuation analysis of nonstationary time series KW - detrended-fluctuation-analysis KW - long-range-correlation KW - multifractality KW - scaling KW - time-series-analysis AU - Kantelhardt, Jan AU - Zschiegner, Stephan AU - Koscielny-Bunde, Eva AU - Bunde, Armin AU - Havlin, Shlomo AU - Stanley, Eugene PY - 2002/Feb/27/ UR - http://arxiv.org/abs/physics/0202070 ER -