Skip to contents

See centralize() for a summary of graph centralization.

Usage

centr_eigen_tmax(graph = NULL, nodes = 0, directed = FALSE, scale = TRUE)

Arguments

graph

The input graph. It can also be NULL, if nodes is given.

nodes

The number of vertices. This is ignored if the graph is given.

directed

logical scalar, whether to use directed shortest paths for calculating betweenness.

scale

Whether to rescale the eigenvector centrality scores, such that the maximum score is one.

Value

Real scalar, the theoretical maximum (unnormalized) graph betweenness centrality score for graphs with given order and other parameters.

See also

Examples

# A BA graph is quite centralized
g <- sample_pa(1000, m = 4)
centr_eigen(g, normalized = FALSE)$centralization %>%
  `/`(centr_eigen_tmax(g))
#> [1] 0.9386488
centr_eigen(g, normalized = TRUE)$centralization
#> [1] 0.9386488