Effect of Trends on Detrended Fluctuation Analysis of Precipitation Series

Yue, Jianhai; Zhao, Xiaochuan; Shang, Pengjian

doi:10.1155/2010/749894

Cited by 21 publications

(6 citation statements)

References 38 publications

(2 reference statements)

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“…The fluctuation component α for healthy old adults is 0.78, for PD subjects is 0.44 and for healthy young adults is 0.68. According to [14], α of PD patients is smaller than 0.5 so there is no correlation; however α of healthy subjects is higher than 0.5 which is interpreted as long range correlation as shown in Fig. 3 and Table II.…”

Section: Resultsmentioning

confidence: 92%

Association of Stride Rate Variability and Altered Fractal Dynamics with Ageing and Neurological Functioning

Channa

Malik

Popescu

2021

2021 23rd International Conference on Control Systems and Computer Science (CSCS)

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Alterations in gait cycle i.e stride rate show fractal dynamics and lower limb walking variability between healthy controls and the controls associated to any neurological disorder. The paper proposes a study in which these stride variability changes in neurological functioning linked with individuals with neurocognitive disorder and accumulation of changes happen in the human body with time called ageing. To validate this research work, we compared the participants' gait cycle in time series: 1) healthy young participants and healthy older adults 2) subjects with Parkinson's disease (PD) and disease-free subjects. Using the Detrended Fluctuation Analysis (DFA) method we computed α, a measure of a degree to which one stride time is compared with the previous and the consecutive intervals over a various time span. The scaling exponent α is exigently curtailed in older adults as compared to young healthy participants. The scaling exponent α is also lower in the subjects with PD compared with the disease-free participants. Moreover, α seems linearly correlated to the degree of functional impairment in subjects with PD. These findings demonstrate that stride time fluctuations are more arbitrary in elderly subjects and in subjects with PD. Abnormal fluctuations in the fractal properties of lower limb dynamics are clearly related to functioning in central nervous system control.

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Section: Resultsmentioning

confidence: 92%

Association of Stride Rate Variability and Altered Fractal Dynamics with Ageing and Neurological Functioning

Channa

Malik

Popescu

2021

2021 23rd International Conference on Control Systems and Computer Science (CSCS)

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“…They used measures based on generalized Hurst exponents to compare financial risks of the market. Yue et al (2010) used detrended fluctuation analysis (DFA) method to detect the long-range correlation and scaling properties of daily precipitation series of Beijing from 1973 to 2004 before and after adding diverse trends to the original series. However, we could not come across studies that have empirically noted direct relationship between the Hurst exponent and predictability of security prices.…”

Section: Literature Surveymentioning

confidence: 99%

Is Hurst Exponent Value Useful in Forecasting Financial Time Series?

Mitra

2012

ASS

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We estimated Hurst exponent of twelve stock index series from across the glove using daily values of for past ten years and found that the Hurst exponent value of the full series is around 0.50 confirming market efficiency. But the Hurst exponent value is found to vary widely when the full series is split into smaller series of 60 trading days. Later, we tried to find relationship between Hurst exponent value and profitable trading opportunity from these smaller series and found that periods displaying high Hurst exponent have potential to yield better trading profits from a moving average trading rule.

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“…In recent years, Detrended Fluctuation Analysis (DFA) (Peng et al 1994) has also been used as an important tool to detect long-range correlations especially in time series with potential nonstationarities. DFA is a scaling analysis method that calculates a quantitative parameter as a representative of the long-range autocorrelation (Yue et al 2010). Moreover, DFA is said to be enabling the correct estimation of the Hurst exponent in the context of nonstationaries (Kantelhardt, 2015).…”

Section: Introductionmentioning

confidence: 99%

Persistence of Rainfall Time Series: Kırşehir Case Study

Oruc¹

2022

Uluslararası Muhendislik Arastirma Ve Gelistirme Dergisi

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This study examines the persistence and long-term correlation of monthly and seasonal precipitation time series of the Kırşehir province (Turkey) for the period of 1960-2019, with the widely used Hurst exponent (H) and Detrended Fluctuation Analysis (DFA) methods. Both methods can be used to detect the long-term memory and correlation to be assessed as a reference of predictability. In order to support the study results, Augmented Dickey Fuller (ADF) and Mann-Kendall (MK) tests were applied to the time series under consideration. In some of the precipitation series, the evidence of persistence and long-term correlation was identified. According to the H exponent values, 10 out of 12 months, winter, and autumn seasons (with both simple R/S and corrected R/S methods), and spring and summer seasons (respectively with simple R/S and corrected R/S methods) exhibit long term correlations. On the other hand, according to the DFA scaling exponent values, 4 out of 12 months, winter and autumn seasons reveal long term correlations. When the H exponent and DFA scaling exponent values are compared only four monthly and two seasonal precipitation series are found to be consistent with each other.

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Effect of Trends on Detrended Fluctuation Analysis of Precipitation Series

Cited by 21 publications

References 38 publications

Association of Stride Rate Variability and Altered Fractal Dynamics with Ageing and Neurological Functioning

Association of Stride Rate Variability and Altered Fractal Dynamics with Ageing and Neurological Functioning

Is Hurst Exponent Value Useful in Forecasting Financial Time Series?

Persistence of Rainfall Time Series: Kırşehir Case Study

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