See centralize
for a summary of graph centralization.
centr_eigen_tmax(graph = NULL, nodes = 0, directed = FALSE, scale = TRUE)
The input graph. It can also be NULL
, if
nodes
is given.
The number of vertices. This is ignored if the graph is given.
logical scalar, whether to use directed shortest paths for calculating betweenness.
Whether to rescale the eigenvector centrality scores, such that the maximum score is one.
Real scalar, the theoratical maximum (unnormalized) graph betweenness centrality score for graphs with given order and other parameters.
Other centralization related:
centr_betw_tmax()
,
centr_betw()
,
centr_clo_tmax()
,
centr_clo()
,
centr_degree_tmax()
,
centr_degree()
,
centr_eigen()
,
centralize()
# NOT RUN {
# A BA graph is quite centralized
g <- sample_pa(1000, m = 4)
centr_eigen(g, normalized = FALSE)$centralization %>%
`/`(centr_eigen_tmax(g))
centr_eigen(g, normalized = TRUE)$centralization
# }
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