See centralize()
for a summary of graph centralization.
Usage
centr_degree_tmax(
graph = NULL,
nodes = 0,
mode = c("all", "out", "in", "total"),
loops = FALSE
)
Arguments
- graph
The input graph. It can also be
NULL
, ifnodes
,mode
andloops
are all given.- nodes
The number of vertices. This is ignored if the graph is given.
- mode
This is the same as the
mode
argument ofdegree()
.- loops
Logical scalar, whether to consider loops edges when calculating the degree. Currently the default value is
FALSE
, but this argument will be required from igraph 1.4.0.
Value
Real scalar, the theoretical maximum (unnormalized) graph degree centrality score for graphs with given order and other parameters.
See also
Other centralization related:
centr_betw()
,
centr_betw_tmax()
,
centr_clo()
,
centr_clo_tmax()
,
centr_degree()
,
centr_eigen()
,
centr_eigen_tmax()
,
centralize()
Examples
# A BA graph is quite centralized
g <- sample_pa(1000, m = 4)
centr_degree(g, normalized = FALSE)$centralization %>%
`/`(centr_degree_tmax(g, loops = FALSE))
#> [1] 0.1599896
centr_degree(g, normalized = TRUE)$centralization
#> [1] 0.1598295