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Bootstrap testing for detrended fluctuation analysis
Physica A: Statistical Mechanics and its Applications, 2006Abstract Detrended fluctuation analysis (DFA) is a scaling method that allows the detection of long memory in a time series. Until now no asymptotic distribution has been found for this statistic. The bootstrap technique allows the simulation of the probability distribution of any statistic.
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Nonlinear filtering properties of detrended fluctuation analysis
Physica A: Statistical Mechanics and its Applications, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ken Kiyono, Yutaka Tsujimoto
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Detrended fluctuation analysis of laser Doppler flowmetry time series
Microvascular Research, 2009Detrended fluctuation analysis (DFA) of laser Doppler flow (LDF) time series appears to yield improved prognostic power in microvascular dysfunction, through calculation of the scaling exponent, alpha. In the present study the long lasting strenuous activity-induced change in microvascular function was evaluated by DFA in basketball players compared ...
Esen, Ferhan +2 more
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A NOVEL CORRELATION FUNCTION FROM DETRENDED FLUCTUATION ANALYSIS
Modern Physics Letters B, 2005A method for investigating the existence of long-range correlations between two sequences is proposed from the detrended fluctuation analysis method. A new correlation function is defined and its behavior is shown for simple examples.
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Detrended fluctuation analysis of heart intrabeat dynamics
Physica A: Statistical Mechanics and its Applications, 2007Abstract We investigate scaling properties of electrocardiogram (ECG) recordings of healthy subjects and heart failure patients based on detrended fluctuation analysis (DFA). While the vast majority of scaling analysis has focused on the characterization of the long-range correlations of interbeat (i.e., beat-to-beat) dynamics, in this work we ...
Eduardo Rodriguez +2 more
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Asymmetric Multifractal Detrended Fluctuation Analysis (A-MFDFA)
2018The presence of multifractality suggests the inefficiency (Cajueiro and Tabak 2004, 2004, 2008; Cajueiro et al. 2009; Tabak and Cajueiro 2007; Wang et al. 2010), volatility predictability (Wei and Wang 2008), crash predictions (Wei and Wang 2008; Grech and Pamula 2008), and complexity (Matia et al. 2003; Kumar and Deo 2009; Norouzzadeh and Jafari 2005)
Guangxi Cao, Ling-Yun He, Jie Cao
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment
Ca-A Cancer Journal for Clinicians, 2022Jun J Mao,, Msce +2 more
exaly
Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma
Ca-A Cancer Journal for Clinicians, 2020Aaron J Grossberg +2 more
exaly