dCor: Distance Correlation for ROI Time Series

In AlexChristensen/NetworkToolbox: Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis

Distance Correlation for ROI Time Series

Description

Computes the distance correlation (Yoo et al., 2019) for ROI time series data. This function is mainly a subroutine for the dCor.parallel function

Usage

dCor(neurallist, centering = c("U", "double"))

Arguments

neurallist	List. A time series list from convertConnBrainMat function
centering	Character. Options for centering the Euclidean distances. "U" Uses number of time points minus 2 in the computation of the mean "double" Uses the mean

Value

Returns a m x m matrix corresponding to distance correlations between ROIs

Author(s)

Alexander Christensen <[e-mail]>

References

Yoo, K., Rosenberg, M. D., Noble, S., Scheinost, D., Constable, R. T., & Chun, M. M. (2019). Multivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors. NeuroImage, 197, 212-223.

Examples

## Not run: 
# Import time series data
neurallist <- convertConnBrainMat()

# Run distance correlation
dCor(neurallist)


## End(Not run)

AlexChristensen/NetworkToolbox documentation built on March 6, 2023, 5:08 p.m.