The Effectiveness Evaluation of Two Kinds of Fractal Sequences on Detrended Fluctuation Analysis
Danying Xie, Li Wan, Yongqiang Zhu
Abstract
Danying Xie, Li Wan, Yongqiang Zhu
Abstract
Used of the fractional Brownian motion and fractional Gaussian noise sequence, the detrended fluctuation analysis (DFA) applied to estimate the Hurst exponent to verify the stability and dependability of the method by changing the data length and regression trend order. The result shows that the Hurst exponent estimate is stable and efficient with the length of data for fractional Brownian motion and fractional Gaussian noise sequence. The influence on the Hurst exponent is not obvious when the regression trend order was changed, and the estimate accuracy is improved with the increasing of Hurst exponent value.
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Used of the fractional Brownian motion and fractional Gaussian noise sequence, the detrended fluctuation analysis (DFA) applied to estimate the Hurst exponent to verify the stability and dependability of the method by changing the data length and regression trend order. The result shows that the Hurst exponent estimate is stable and efficient with the length of data for fractional Brownian motion and fractional Gaussian noise sequence. The influence on the Hurst exponent is not obvious when the regression trend order was changed, and the estimate accuracy is improved with the increasing of Hurst exponent value.
Key concepts: Detrended fluctuation analysis, Hurst exponent, Fractional Brownian motion, Mathematics, Fractal, Statistical physics, Statistics, Exponent