current_centr_mult: Find current-flow closeness centrality for a list of graphs

In abnormally-distributed/rsfcNet: Analyze resting state functional connectivity networks

Description

A variant of closeness centrality based on circuits

Usage

current_centr_mult(
  graphs,
  col.names = NULL,
  row.names = NULL,
  parallel = TRUE,
  cores = NA
)

Arguments

graphs	A list of igraph objects or connectivity matrices
col.names	The names of each column (node labels).
row.names	The names of each row (subject).
parallel	Should multiple cores be used? Defaults to FALSE. If TRUE, progress bar is not displayed. This is normal.
cores	How many cores should be used? Defaults to recommended 1 less than number of CPU cores.

Details

Current flow centrality was developed based on the properties of electrical circuits. It is a variant of closeness centrality that imagines edges resistors and the nodes as relays between resistors. Weighted edge information is taken into account as the absolute value. Non-zero edge are conceptually "conductors" while zero edges are "resistors."

Current flow centrality is somewhat mathematically involved, but the final formula is

\displaystyle{∑_j A_{i,j} (v_{i}^{(s,t)} - v_{j}^{(s,t)}) = u_{i}^{(s,t)}}$.

See the website in the references for a full explanation. The method involves calculating the laplacian representation of a graph.

Value

A matrix contaning the centrality scores.

Author(s)

Brandon Vaughan

References

Brandes U., Fleischer D. (2005) Centrality Measures Based on Current Flow. In: Diekert V., Durand B. (eds) STACS 2005. STACS 2005. Lecture Notes in Computer Science, vol 3404. Springer, Berlin, Heidelberg

https://www.sci.unich.it/~francesc/teaching/network/flowcentrality.html

See Also

closeness_centr laplace_centr_mult current_centr

Examples

current_centr_mult(graph)

abnormally-distributed/rsfcNet documentation built on March 8, 2020, 5:32 p.m.