Time-lagged Correlationdoi:10.1007/978-1-4419-9863-7_101505Time-delay CorrelationWerner DubitzkyOlaf WolkenhauerKwangHyun ChoHiroki YokotaSpringer New York
rapidtide- This is the heart of the package - this is the workhorse program that will determine the time lagged correlations between all the voxels in a NIFTI file and a temporal "probe" regressor (which can come from a number of places, including the data itself) - it rapidly determines...
The time-lagged correlations were stronger, suggesting that the employee turnover has a long-term impact on the performance. The relationship between employee turnover and restaurant performance was found to be stronger for those restaurant concepts with a high level of service. Future turnover ...
The detrended time-lagged cross-correlation analysis A time-lagged DCCA cross-correlation coefficient is proposed with objective of quantifying the level of time-lagged cross-correlation between two nonstationary time series at time scales. This coefficient, ρ(n, τ, R, R ), is defi...
Detrended time-lagged cross-correlation analysis between time series is studied.Time-lagged DCCA cross-correlation coefficient is defined and applied in meteorology.ρ(n,τ,R,R′) is attributed to time delay effect and ρDCCA.Contribution to ρ(n,τ,R,R′) from ρDCCA is greater for τ<n ...
Lagged correlation (see Figure, panel b) here yields spurious associations between X and Z due to Y acting as a common driver. Furthermore, Y and W are correlated via an indirect path Y\(\rightarrow\)Z\(\rightarrow\)W, and X and W are also spuriously correlated. Multivariate Granger ...
This form can be generalized to multivariate cases vector (yt), including exogenous inputs such as control signals, and correlation effects in the residues. For more difficult cases, the linear relationship can be replaced by a nonlinear one yt=f(Xt,et), where f() is a nonlinear function ...
autocorrelation, it is very sensitive to other model misspecifications. That is, it is powerful against many alternatives for which the test is not designed. It is also invalid in the presence of lagged response variables (see the exampleTime Series Regression VIII: Lagged Variables and Estimator...
To address this, we propose an imputation method (FLk-NN) that incorporates time lagged correlations both within and across variables by combining two imputation methods, based on an extension to k-NN and the Fourier transform. This enables imputation of missing values even when all data at a...
Lagged correlation (see Figure, panel b) here yields spurious associations between X and Z due to Y acting as a common driver. Furthermore, Y and W are correlated via an indirect path Y\(\rightarrow\)Z\(\rightarrow\)W, and X and W are also spuriously correlated. Multivariate Granger ...