Add to ORKGWemake the comparative study of scaling range properties for detrended fluctuation analysis (DFA), detrended moving average analysis (DMA) and recently proposed new technique called modified detrended moving average analysis (MDMA). Basic properties of scaling ranges for these techniques are reviewed. The efficiency and exactness of all three methods towards proper determination of scaling Hurst exponent H is discussed, particularly for short series of uncorrelated and persistent data
H = DFA(X) calculates the Hurst exponent of time series X using Detrended Fluctuation Analysis (DFA)...
The origin and the properties of crossovers in the scaling behavior of noisy signals were studied by...
Detrended fluctuation analysis (DFA) is one of the most frequently used fractal time series algorit...
We make the comparative study of scaling range properties for detrended fluctuation analysis (DFA), ...
Detrended fluctuation analysis (DFA) and detrended moving average (DMA) are two scaling analysis met...
The Detrending Moving Average (DMA) algorithm has been widely used in its several variants for chara...
Long-range correlation properties of financial stochastic time series y(i) have been, investigated w...
The Hurst exponent $H$ of long range correlated series can be estimated by means of the Detrending M...
We present a bottom-up derivation of fluctuation analysis with detrending for the detection of long-...
<p>(A, C) Time series of the state variable. (B, D). DFA estimated within rolling windows of half th...
We develop a criterion based on a brute-force algorithm to systematically determine optimal fitting ...
<p>For each Hurst exponent, statistical average and fluctuation are obtained over an ensemble of in...
Detrended Fluctuation Analysis (DFA) has become a standard method to quantify the correlations and s...
Detrended fluctuation analysis (DFA) is a technique commonly used to assess and quantify the pres- e...
Scaling properties are among the most important quantifiers of complexity in many real systems, incl...
H = DFA(X) calculates the Hurst exponent of time series X using Detrended Fluctuation Analysis (DFA)...
The origin and the properties of crossovers in the scaling behavior of noisy signals were studied by...
Detrended fluctuation analysis (DFA) is one of the most frequently used fractal time series algorit...
We make the comparative study of scaling range properties for detrended fluctuation analysis (DFA), ...
Detrended fluctuation analysis (DFA) and detrended moving average (DMA) are two scaling analysis met...
The Detrending Moving Average (DMA) algorithm has been widely used in its several variants for chara...
Long-range correlation properties of financial stochastic time series y(i) have been, investigated w...
The Hurst exponent $H$ of long range correlated series can be estimated by means of the Detrending M...
We present a bottom-up derivation of fluctuation analysis with detrending for the detection of long-...
<p>(A, C) Time series of the state variable. (B, D). DFA estimated within rolling windows of half th...
We develop a criterion based on a brute-force algorithm to systematically determine optimal fitting ...
<p>For each Hurst exponent, statistical average and fluctuation are obtained over an ensemble of in...
Detrended Fluctuation Analysis (DFA) has become a standard method to quantify the correlations and s...
Detrended fluctuation analysis (DFA) is a technique commonly used to assess and quantify the pres- e...
Scaling properties are among the most important quantifiers of complexity in many real systems, incl...
H = DFA(X) calculates the Hurst exponent of time series X using Detrended Fluctuation Analysis (DFA)...
The origin and the properties of crossovers in the scaling behavior of noisy signals were studied by...
Detrended fluctuation analysis (DFA) is one of the most frequently used fractal time series algorit...