centralization.evcent: Centralize a graph according to the eigenvector centrality of...

In igraph: Network Analysis and Visualization

Centralize a graph according to the eigenvector centrality of vertices

Description

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

Usage

centralization.evcent(
  graph,
  directed = FALSE,
  scale = TRUE,
  options = arpack_defaults(),
  normalized = TRUE
)

Arguments

graph	The input graph.
directed	logical scalar, whether to use directed shortest paths for calculating eigenvector centrality.
scale	Whether to rescale the eigenvector centrality scores, such that the maximum score is one.
options	This is passed to eigen_centrality(), the options for the ARPACK eigensolver.
normalized	Logical scalar. Whether to normalize the graph level centrality score by dividing by the theoretical maximum.

igraph documentation built on Oct. 20, 2024, 1:06 a.m.