See `centralize()`

for a summary of graph centralization.

## Usage

```
centr_degree_tmax(
graph = NULL,
nodes = 0,
mode = c("all", "out", "in", "total"),
loops
)
```

## 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.

- mode
This is the same as the

`mode`

argument of`degree()`

. Ignored if`graph`

is given and the graph is undirected.- loops
Logical scalar, whether to consider loops edges when calculating the degree.

## 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
```