centrality_percolation: Percolation Centrality

In cograph: Analysis and Visualization of Complex Networks

Percolation Centrality

Description

Importance for spreading processes using node states. Each node has a state (0-1) representing how activated it is. When all states are equal, equivalent to betweenness.

Usage

centrality_percolation(x, states = NULL, ...)

Arguments

x	Network input (matrix, igraph, network, cograph_network, tna object).
states	Named numeric vector of node states (0-1). Default NULL (all nodes get state 1).
...	Additional arguments passed to centrality (e.g., weighted, directed).

Value

Named numeric vector of percolation centrality values.

See Also

centrality for computing multiple measures at once, centrality_betweenness which this generalizes.

Examples

adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), 3, 3)
rownames(adj) <- colnames(adj) <- c("A", "B", "C")
centrality_percolation(adj)
centrality_percolation(adj, states = c(A = 0.8, B = 0.2, C = 0.5))

cograph documentation built on April 1, 2026, 1:07 a.m.