Coupling detrended fluctuation analysis for analyzing coupled nonstationary signals

被引:66
作者
Hedayatifar, L. [1 ]
Vahabi, M. [1 ]
Jafari, G. R. [1 ]
机构
[1] Shahid Beheshti Univ, Dept Phys, GC, Tehran 19839, Iran
来源
PHYSICAL REVIEW E | 2011年 / 84卷 / 02期
关键词
AIR-POLLUTANT CONCENTRATION; LONG-RANGE DEPENDENCE; MULTIFRACTAL ANALYSIS; CROSS-CORRELATIONS; TIME-SERIES; PRICE; TEMPERATURE; DYNAMICS; YIELD; STOCK;
D O I
10.1103/PhysRevE.84.021138
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
When many variables are coupled to each other, a single case study could not give us thorough and precise information. When these time series are stationary, different methods of random matrix analysis and complex networks can be used. But, in nonstationary cases, the multifractal-detrended-cross-correlation-analysis (MF-DXA) method was introduced for just two coupled time series. In this article, we have extended the MF-DXA to the method of coupling detrended fluctuation analysis (CDFA) for the case when more than two series are correlated to each other. Here, we have calculated the multifractal properties of the coupled time series, and by comparing CDFA results of the original series with those of the shuffled and surrogate series, we can estimate the source of multifractality and the extent to which our series are coupled to each other. We illustrate the method by selected examples from air pollution and foreign exchange rates.
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页数:7
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