clustered.graphs: Cluster ego-centered networks by a grouping factor
In tilltnet/egonetR: Import and analyse ego-centric network data

Description Usage Arguments Value References See Also Examples

The idea of clustered graphs is to reduce the complexity of an ego-centered network graph by visualising its group aggregated form. It is developed by Lerner et al. (2008). It helps to discover and visualise structural and compostional properties of ego-centered networks, based on a pre-defined factor variable on the alter level. clustered.graphs() calculates group sizes, inter- and intragroup densities and these informations in a list of igraph objects.

1	clustered.graphs(alteri.list, edges.list, clust.groups)

`alteri.list`	`List` of `data frames` containing the alteri data.
`edges.list`	`List` of `data frames` containing the edge lists (= alter-alter relations).
`clust.groups`	A `character` naming the `factor` variable building the groups.

clustered.graphs returns a list of graph objects representing the clustered ego-centered network data;

Brandes, U., Lerner, J., Lubbers, M. J., McCarty, C., & Molina, J. L. (2008). Visual Statistics for Collections of Clustered Graphs. 2008 IEEE Pacific Visualization Symposium, 47-54.

vis.clustered.graphs for visualising clustered graphs

data("egoR32")

# Simplify networks to clustered graphs, stored as igraph objects
graphs <- clustered.graphs(egoR32$alteri.list, egoR32$edges, "alter.age") 

# Visualise
vis.clustered.graphs(graphs)