Detrended partial cross-correlation analysis of age-related changes

Liu, Chia‐Ju; Jhone, Yan-Lin; Chih-Chieh, Hsu; Teng, Pei-ching; Lu, Ming-Chi; Yang, Chih-Hung; Ho, Ming‐Chung

doi:10.1109/icamse.2016.7840300

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…erefore, Liu et al first applied it to the research related to age changes. By calculating the DPCCA coefficient to explore the age-related changes of event-related potentials, they found that the DPCCA coefficient between young people and old people is different with different neural communication methods [36].…”

Section: Introductionmentioning

confidence: 99%

Dollar’s Influence on Crude Oil and Gold Based on MF-DPCCA Method

Ding

Shi

Wang

2021

Discrete Dynamics in Nature and Society

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This paper analyzed the influence of dollar on crude oil and gold based on the multifractal detrended partial cross-correlation analysis method. It showed that affected by the dollar, the crude oil and gold markets have a partial cross-correlation relationship which is stronger than their own cross-correlation. The partial cross-correlation is long-term and has multifractal characteristics. Through shuffled and Fourier-phase randomization, it is found that this multifractal feature is caused by the combined effect of the long-term cross-correlation between the returns and the fluctuation fat-tailed distribution, where the influence of the fat-tailed distribution is slightly greater than that of the long-term cross-correlation between the returns.

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Section: Introductionmentioning

confidence: 99%

Dollar’s Influence on Crude Oil and Gold Based on MF-DPCCA Method

Ding

Shi

Wang

2021

Discrete Dynamics in Nature and Society

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Section: Introductionmentioning

confidence: 99%

“…Yan et al (2017) employed the DPCCA to investigate horizontal oil-water two-phase flow structures, and found that DPCCA cross-correlation coefficient can serve as an effective indicator of horizontal oil-water two-phase flow structures [21]. Liu et al (2017) investigated age-related changes of event-related potentials with DPCCA to explore the discrimination between the young and the older [22].Afterward, the TDCCA and TDPCCA were successively proposed based on DCCA and DPCCA, by which it is feasible to explore the correlations on multi-time scales and at different periods. However, they are rarely introduced and applied into hydrological fields to study the temporal evolution of correlation between hydro-meteorological variables, though the cross-correlation analysis methods for non-stationary series have been developed rapidly in recent years.…”

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confidence: 99%

Intrinsic Cross-Correlation Analysis of Hydro-Meteorological Data in the Loess Plateau, China

Wei

Zhang

Gong

et al. 2020

IJERPH

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The purpose of this study is to illustrate intrinsic correlations and their temporal evolution between hydro-meteorological elements by building three-element-composed system, including precipitation (P), runoff (R), air temperature (T), evaporation (pan evaporation, E), and sunshine duration (SD) in the Wuding River Basin (WRB) in Loess Plateau, China, and to provide regional experience to correlational research of global hydro-meteorological data. In analysis, detrended partial cross-correlation analysis (DPCCA) and temporal evolution of detrended partial-cross-correlation analysis (TDPCCA) were employed to demonstrate the intrinsic correlation, and detrended cross-correlation analysis (DCCA) coefficient was used as comparative method to serve for performance tests of DPCCA. In addition, a novel way was proposed to estimate the contribution of a variable to the change of correlation between other two variables, namely impact assessment of correlation change (IACC). The analysis results in the WRB indicated that (1) DPCCA can analyze the intrinsic correlations between two hydro-meteorological elements by removing potential influences of the relevant third one in a complex system, providing insights on interaction mechanisms among elements under changing environment; (2) the interaction among P, R, and E was most strong in all three-element-composed systems. In elements, there was an intrinsic and stable correlation between P and R, as well as E and T, not depending on time scales, while there were significant correlations on local time scales between other elements, i.e., P-E, R-E, P-T, P-SD, and E-SD, showing the correlation changed with time-scales; (3) TDPCCA drew and highlighted the intrinsic correlations at different time-scales and its dynamics characteristic between any two elements in the P-R-E system. The results of TDPCCA in the P-R-E system also demonstrate the nonstationary correlation and may give some experience for improving the data quality. When establishing a hydrological model, it is suitable to only use P, R, and E time series with significant intrinsic correlation for calibrating model. The IACC results showed that taking pan evaporation as the representation of climate change (barring P), the impacts of climate change on the non-stationary correlation of P and R was estimated quantitatively, illustrating the contribution of climate to the correlation variation was 30.9%, and that of underlying surface and direct human impact accounted for 69.1%. IntroductionComplex hydro-meteorological systems contain various interactions among hydro-meteorological elements [1,2]. Investigating cross-correlations and teleconnections between hydro-meteorological signals benefits to deeply understanding the whole hydrological system and to serve for water resources management [3]. Under the influences of changing climate and anthropogenic disturbance [4], the single hydro-meteorological time series and their interaction relationships tend to exhibit complex [5,6], non-stationary [7], and multi-scale [8] chang...

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Detrended partial cross-correlation analysis of age-related changes

Cited by 2 publications

References 7 publications

Dollar’s Influence on Crude Oil and Gold Based on MF-DPCCA Method

Dollar’s Influence on Crude Oil and Gold Based on MF-DPCCA Method

Intrinsic Cross-Correlation Analysis of Hydro-Meteorological Data in the Loess Plateau, China

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