Triadic Synchrony: Application of Multiple Wavelet Coherence to a Small Group Conversation

By applying multiple wavelet coherence (MWC) to data from human body movements in triadic interaction, this study quantified triadic synchrony, rhythmic similarity among three interactants. Thirty-nine Japanese undergraduates were randomly assigned in a triad, and engaged in a brain-storming task. Triadic synchrony was quantified by calculating MWC to the time-series movement data collected by Kinect v2 sensor. The existence of synchrony was statistically tested by using a pseudo-synchrony paradigm. Results showed that the averaged value of MWC was higher in the experimental participant trio than in those of the pseudo trio in the frequency band of 0.5 - 1 Hz. The result supports the possible utility of applying multiple wavelet coherence to evaluate triadic synchrony in a small group interaction.

Synergistic effects of multiple driving factors on the runoff variations in the Yellow River Basin,China

River runoff plays an important role in watershed ecosystems and human survival,and it is controlled by multiple environmental factors.However,the synergistic effects of various large-scale circulation factors and meteorological factors on the runoff on different time-frequency scales have rarely been explored.In light of this,the underlying mechanism of the synergistic effects of the different environmental factors on the runoff variations was investigated in the Yellow River Basin of China during the period 1950-2019 using the bivariate wavelet coherence(WTC)and multiple wavelet coherence(MWC)methods.First,the continuous wavelet transform(CWT)method was used to analyze the multiscale characteristics of the runoff.The results of the CWT indicate that the runoff exhibited significant continuous or discontinuous annual and semiannual oscillations during the study period.Scattered inter-annual time scales were also observed for the runoff in the Yellow River Basin.The meteorological factors better explained the runoff variations on seasonal and annual time scales.The average wavelet coherence(AWC)and the percent area of the significant coherence(PASC)between the runoff and individual meteorological factors were 0.454 and 19.89%,respectively.The circulation factors mainly regulated the runoff on the inter-annual and decadal time scales with more complicated phase relationships due to their indirect effects on the runoff.The AWC and PASC between the runoff and individual circulation factors were 0.359 and 7.31%,respectively.The MWC analysis revealed that the synergistic effects of multiple factors should be taken into consideration to explain the multiscale characteristic variations of the runoff.The AWC or MWC ranges were 0.320-0.560,0.617-0.755,and 0.819-0.884 for the combinations of one,two,and three circulation and meteorological factors,respectively.The PASC ranges were 3.53%-33.77%,12.93%-36.90%,and 20.67%-39.34%for the combinations one,two,and three driving factors,respectively.The combinations of precipitation,evapotranspiration(or the number of rainy days),and the Arctic Oscillation performed well in explaining the variability in the runoff on all time scales,and the average MWC and PASC were 0.847 and 28.79%,respectively.These findings are of great significance for improving our understanding of hydro-climate interactions and water resources prediction in the Yellow River Basin.

Modeling and forecasting time series of precious metals:a new approach to multifractal data

We introduce a novel approach to multifractal data in order to achieve transcended modeling and forecasting performances by extracting time series out of local Hurst exponent calculations at a specified scale.First,the long range and co-movement dependencies of the time series are scrutinized on time-frequency space using multiple wavelet coherence analysis.Then,the multifractal behaviors of the series are verified by multifractal de-trended fluctuation analysis and its local Hurst exponents are calculated.Additionally,root mean squares of residuals at the specified scale are procured from an intermediate step during local Hurst exponent calculations.These internally calculated series have been used to estimate the process with vector autoregressive fractionally integrated moving average(VARFIMA)model and forecasted accordingly.In our study,the daily prices of gold,silver and platinum are used for assessment.The results have shown that all metals do behave in phase movement on long term periods and possess multifractal features.Furthermore,the intermediate time series obtained during local Hurst exponent calculations still appertain the co-movement as well as multifractal characteristics of the raw data and may be successfully re-scaled,modeled and forecasted by using VARFIMA model.Conclusively,VARFIMA model have notably surpassed its univariate counterpart(ARFIMA)in all efficacious trials while re-emphasizing the importance of comovement procurement in modeling.Our study’s novelty lies in using a multifractal de-trended fluctuation analysis,along with multiple wavelet coherence analysis,for forecasting purposes to an extent not seen before.The results will be of particular significance to finance researchers and practitioners.