The statistical properties of the cross correlation between two time series has been studied. An analytical expression for the cross correlation function's variance has been derived. On the basis of these results, a statistically robust method has been proposed to detect the existence and determine ...
Consistent results are obtained by comparing the new method with the detrended cross-correlation coefficient蟻DCCA. Therefore, the proposed approach is reliable, reasonable, and applicable, and can examine the degree of the local intrinsic cross-correlation between two nonstationary time series....
One way to decide this is to look at the correlation between the two time series at various lags and identify the lag that produces the highest correlation coefficient, or assuming that there can be an inverse correlation between the two time series, the highest correlation in absolute value. ...
The vertical crosscorrelation between two time series of wind speed in different heights gives information about the slope of the eddyfront. The larger the distance between the two heights, the weeker is the peak of the crosscorrelation as is shown in figure 3. The maximum of the crosscorrelat...
Cross-correlation is generally used when measuring information between two different time series. The possible range for thecorrelation coefficientof the time series data is from -1.0 to +1.0. The closer the cross-correlation value is to 1, the more closely the sets are identical. ...
Multiscale Multifractal Detrended Cross-Correlation Analysis of High-Frequency Financial Time Series In order to obtain richer information on the cross-correlation properties between two time series, we introduce a method called multiscale multifractal det... J Huang,D Gu - 《Fluctuation & Noise Lette...
Test I shows the advantages of DPCCA in handling non-stationary signals, while Test II reveals the “intrinsic” relations between two considered time series with potential influences of other unconsidered signals removed. To further show the utility of DPCCA in natural complex systems, we provide...
Recurrence Quantification Analysis for Categorical and Continuous Time-Series [R package crqa version 2.0.1] Description CRQA is a package to perform cross-recurrence quantification analysis between two time-series, of either categorical or continuous values. It provides different methods for profiling ...
Obtain the magnitude-squared coherence estimate for the bivariate time series. The magnitude-squared coherence enables you to identify significant frequency-domain correlation between the two time series. Phase estimates in the cross spectrum are only useful where significant frequency-domain correlation exi...
JOURNAL OF Development ECONOMICS Openness and growth: A time-series, cross-country analysis for developing countries This paper draws together a variety of openness measures to test the association between openness and growth. Although the correlation across different types of openness is not always ...