`gden`

computes the density of the graphs indicated by `g`

in collection `dat`

, adjusting for the type of graph in question.

`gden(dat, g=NULL, diag=FALSE, mode="digraph", ignore.eval=FALSE)`

dat

one or more input graphs.

g

integer indicating the index of the graphs for which the density is to be calculated (or a vector thereof). If `g==NULL`

(the default), density is calculated for all graphs in `dat`

.

diag

boolean indicating whether or not the diagonal should be treated as valid data. Set this true if and only if the data can contain loops. `diag`

is `FALSE`

by default.

mode

string indicating the type of graph being evaluated. "digraph" indicates that edges should be interpreted as directed; "graph" indicates that edges are undirected. `mode`

is set to "digraph" by default.

ignore.eval

logical; should edge values be ignored when calculating density?

The graph density

The density of a graph is here taken to be the sum of tie values divided by the number of possible ties (i.e., an unbiased estimator of the graph mean); hence, the result is interpretable for valued graphs as the mean tie value when `ignore.eval==FALSE`

. The number of possible ties is determined by the graph type (and by `diag`

) in the usual fashion.

Where missing data is present, it is removed prior to calculation. The density/graph mean is thus taken relative to the observed portion of the graph.

Wasserman, S., and Faust, K. (1994). *Social Network Analysis: Methods and Applications.* Cambridge: Cambridge University Press.

```
# NOT RUN {
#Draw three random graphs
dat<-rgraph(10,3)
#Find their densities
gden(dat)
# }
```

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