Detrended cross correlation analysis (DCCA) of radon, thoron, temperature and pressure time series data

2020 ◽  
Vol 95 (8) ◽  
pp. 085213
Author(s):  
Javid Iqbal ◽  
Kashif Javed Lone ◽  
Lal Hussain ◽  
Muhammad Rafique
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
Cross Correlation ◽  
Time Series Data ◽  
Series Data ◽  
Pressure Time ◽  
Cross Correlation Analysis ◽  
Temperature And Pressure

scholarly journals Dynamical Characteristics in Time Series Between PM10 and Wind Speed

2021 ◽  
Vol 15 ◽  
pp. 26-30
Author(s):  
Deok Du Kang ◽  
Dong In Lee ◽  
Jae-Won Jung ◽  
Kyungsk Kim
Keyword(s):  
Time Series ◽  
Wind Velocity ◽  
Cross Correlation ◽  
Time Series Data ◽  
Series Data ◽  
South Korean ◽  
Dynamical Characteristics ◽  
Cross Correlation Analysis ◽  
Variation Characteristics ◽  
Dust Events

We study the temporal variation characteristics of PM10 and wind velocity in eight South Korean cities. We employ the detrended cross-correlation analysis (DCCA) method to extract the overall tendency of the hourly variation. We ascertain from three-daily and one-weekly intervals that Busan has the negative largest, while Donghae has the positive largest in the DCCA cross-correlation coefficient between PM10 and wind velocity. As a result of Asian dust events, the cross-correlation is statistically significant for the hourly time series data less than two days. Particularly, we discuss whether a cross-correlation is statistically significant or not from random number surrogation and shuffled time series surrogation

scholarly journals Lateral and longitudinal chloride dynamics in an urbanizing watershed in Southern Ontario: a spatial cross-correlation modelling approach

2021 ◽  
Author(s):  
Bhaswati Mazumder
Keyword(s):  
Time Series ◽  
Cross Correlation ◽  
Hyporheic Zone ◽  
Time Series Data ◽  
Urban Stream ◽  
Series Data ◽  
Catchment Scale ◽  
Southern Ontario ◽  
Urbanizing Watershed ◽  
Correlation Modelling

The application of spatial cross-correlation modelling was tested on continuous time series of electrical conductivity to estimate lateral and longitudinal chloride dynamics in an urbanizing watershed in Southern Ontario. Overall, the model appeared more robust for the winter salting season than for the summer growing season. The winter results showed shorter travel times with higher velocity longitudinally (upstream to downstream) in an urban stream reach with more impervious surfaces than in a rural reach with more permeable surfaces. The lateral exchange rates (stream-hyporheic zone) were observed to be affected by both local and catchment-scale land use and soil profiles. Cross-correlation results and time series data also indicated that road-salt applications in the urban catchment may be leading to underground storage of chloride, contributing to the streams in summer and producing year-round peaks of chloride in the urban stream reach.

Correlation analysis of continuous emotional response to music: Correcting for the effects of serial correlation

2001 ◽  
Vol 5 (1_suppl) ◽  
pp. 213-236 ◽  
Author(s):  
Emery Schubert
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
Emotional Response ◽  
Serial Correlation ◽  
Time Series Data ◽  
Second Order ◽  
Series Data ◽  
First Order ◽  
The Relationship ◽  
Pearson Correlations

Publications of research concerning continuous emotional responses to music are increasing. The developing interest brings with it a need to understand the problems associated with the analysis of time series data. This article investigates growing concern in the use of conventional Pearson correlations for comparing time series data. Using continuous data collected in response to selected pieces of music, with two emotional dimensions for each piece, two falsification studies were conducted. The first study consisted of a factor analysis of the individual responses using the original data set and its first-order differenced transformation. The differenced data aligned according to theoretical constraints better than the untransformed data, supporting the use of first-order difference transformations. Using a similar method, the second study specifically investigated the relationship between Pearson correlations, difference transformations and the critical correlation coefficient above which the conventional correlation analysis remains internally valid. A falsification table was formulated and quantified through a hypothesis index function. The study revealed that correlations of undifferenced data must be greater than 0.75 for a valid interpretation of the relationship between bivariate emotional response time series data. First and second-order transformations were also investigated and found to be valid for correlation coefficients as low as 0.24. Of the three version of the data (untransformed, first-order differenced, and second-order differenced), first-order differenced data produced the fewest problems with serial correlation, whilst remaining a simple and meaningful transformation.

Multiscale Multifractal Detrended Cross-Correlation Analysis of High-Frequency Financial Time Series

2019 ◽  
Vol 18 (03) ◽  
pp. 1950014 ◽  
Author(s):  
Jingjing Huang ◽  
Danlei Gu
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
High Frequency ◽  
Cross Correlation ◽  
Financial Time Series ◽  
Chinese Market ◽  
Change Of Scale ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross

In order to obtain richer information on the cross-correlation properties between two time series, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). This method is based on the Hurst surface and can be used to study the non-linear relationship between two time series. By sweeping through all the scale ranges of the multifractal structure of the complex system, it can present more information than the multifractal detrended cross-correlation analysis (MF-DCCA). In this paper, we use the MM-DCCA method to study the cross-correlations between two sets of artificial data and two sets of 5[Formula: see text]min high-frequency stock data from home and abroad. They are SZSE and SSEC in the Chinese market, and DJI and NASDAQ in the US market. We use Hurst surface and Hurst exponential distribution histogram to analyze the research objects and find that SSEC, SZSE and DJI, NASDAQ all show multifractal properties and long-range cross-correlations. We find that the fluctuation of the Hurst surface is related to the positive and negative of [Formula: see text], the change of scale range, the difference of national system, and the length of time series. The results show that the MM-DCCA method can give more abundant information and more detailed dynamic processes.

Importance of Body Sway Velocity Information in Controlling Ankle Extensor Activities During Quiet Stance

2003 ◽  
Vol 90 (6) ◽  
pp. 3774-3782 ◽  
Author(s):  
Kei Masani ◽  
Milos R. Popovic ◽  
Kimitaka Nakazawa ◽  
Motoki Kouzaki ◽  
Daichi Nozaki
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
Muscle Activity ◽  
Cross Correlation ◽  
Gastrocnemius Muscle ◽  
Quiet Stance ◽  
Lateral Gastrocnemius ◽  
Velocity Feedback ◽  
Cross Correlation Analysis ◽  
Velocity Information

In literature, it has been suggested that the CNS anticipates spontaneous change in body position during quiet stance and continuously modulates ankle extensor muscle activity to compensate for the change. The purpose of this study was to investigate whether velocity feedback contributes by modulating ankle extensor activities in an anticipatory fashion, facilitating effective control of quiet stance. Both theoretical analysis and experiments were carried out to investigate to what extent velocity feedback contributes to controlling quiet stance. The experiments were carried out with 16 healthy subjects who were asked to stand quietly with their eyes open or closed. During the experiments, the center of pressure (COP) displacement (COPdis), the center of mass (COM) displacement (COMdis), and COM velocity (COMvel) in the anteroposterior direction were measured. Rectified electromyograms (EMGs) were used to measure muscle activity in the right soleus muscle, the medial gastrocnemius muscle, and the lateral gastrocnemius muscle. The simulations were performed using an inverted pendulum model that described the anteroposterior kinematics and dynamics of quiet stance. In the simulations, an assumption was made that the COMdis of the body would be regulated using a proportional-derivative (PD) controller. Two different PD controllers were evaluated in these simulations: 1) a controller with the high-derivative/velocity gain (HDG) and 2) a controller with the low-derivative/velocity gain (LDG). Cross-correlation analysis was applied to investigate the relationships between time series obtained in experiments 1) COMdis and EMGs and 2) COMvel and EMGs. Identical cross-correlation analysis was applied to investigate the relationships between time series obtained in simulations 3) COMdis and ankle torque and 4) COMvel and ankle torque. The results of these analyses showed that the COMdis was positively correlated with all three EMGs and that the EMGs temporally preceded the COMdis. These findings agree with the previously published studies in which it was shown that the lateral gastrocnemius muscle is actively modulated in anticipation of the body's COM position change. The COMvel and all three EMGs were also correlated and the cross-correlation function (CCF) had two peaks: one that was positive and another that was negative. The positive peaks were statistically significant, unlike the negative ones; they were larger than the negative peaks; and their time shifts were much shorter compared with the time shifts of the negative peaks. When these results were compared with the CCF results obtained for simulated time series, it was discovered that the cross-correlation results for the HDG controller closely matched cross-correlation results for the experimental time series. On the other hand, the simulation result obtained for LDG controller did not match the experimental results. These findings suggest that the actual postural control system during quiet stance adopts a control strategy that relies notably on velocity information and that such a controller can modulate muscle activity in anticipatory manner without using a feed-forward mechanism.

scholarly journals Total Imports and Its Components Influence on Inflation in Kenya

2020 ◽  
pp. 54-62
Author(s):  
Evans Ovamba Kiganda ◽  
Margaret Atieno Omondi
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
Central Bank ◽  
Granger Causality ◽  
Time Series Data ◽  
Negative Influence ◽  
Variance Decomposition ◽  
Series Data ◽  
Causality Tests ◽  
Granger Causality Tests

Aim: The purpose of this study was to analyze the influence of total imports (TIMP) and its components of commercial imports (CIMP) and government imports (GIMP) on inflation in           Kenya. Study Design: Quantitative approach was employed to analyze the influence of imports on inflation in Kenya. Methodology: Monthly time series data from Central Bank of Kenya for the period 2005 to 2018 was used for analysis involving correlation analysis, variance decomposition, impulse response and Granger causality tests. Results: Results indicated that total imports and commercial imports had negative influence on inflation while government imports did not significantly influence inflation in Kenya. Unidirectional causality from total imports and commercial imports to inflation was noted while there was no causality between government imports and inflation. Conclusion: The study concluded that imports influence inflation in Kenya but commercial imports highly determined total imports influence on inflation in Kenya.

scholarly journals An Outlier Detection Algorithm Based on Cross-Correlation Analysis for Time Series Dataset

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 53593-53610 ◽  
Author(s):  
Hui Lu ◽  
Yaxian Liu ◽  
Zongming Fei ◽  
Chongchong Guan
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
Outlier Detection ◽  
Cross Correlation ◽  
Detection Algorithm ◽  
Time Series Dataset ◽  
Cross Correlation Analysis
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