centralization.evcent.tmax: Theoretical maximum for betweenness centralization

In igraph/rigraph: Network Analysis and Visualization

Theoretical maximum for betweenness centralization

Description

centralization.evcent.tmax() was renamed to centr_eigen_tmax() to create a more consistent API.

Usage

centralization.evcent.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 consider edge directions during the calculation. Ignored in undirected graphs.
scale	Ignored. Computing eigenvector centralization requires normalized eigenvector centrality scores.

igraph/rigraph documentation built on June 13, 2025, 1:44 p.m.