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## IntroductionEdit

We mainly use following packages to demontrate network analysis in R: **statnet**, **sna**, **igraph**. They are however not representing a complete list. See Task view of *gR*, graphical models in R for a complete list.

## Creating simple graphs with igraphEdit

> # load the appropriate library > library(igraph) > # now create a few simple graphs > g <- graph.empty(10,directed=FALSE) > g2 <- graph.ring(10,directed=TRUE) > g3 <- graph.full(10,directed=FALSE) > # now get information about these graphs > summary(g)

## Creating graphs from dataEdit

First load the igraph package

library(igraph)

then you can choose your preferred format. Below are examples of data provided as edge list and as adjacency matrix.

### Creating graph from an edge listEdit

An edge list is formed by a two-column matrix, with each row defining one edge. An edge is drawn from each element in the first column to the corresponding element in the second one. Use the `graph.edgelist()`

function to import your data.

# producing some random data in edge list form el <- cbind(sample(1:10, 10), sample(1:10, 10)) # creating and plottig the graph from the edge list gr <- graph.edgelist(el) plot(gr)

### Creating graph from an adjacency matrixEdit

An adjacency matrix is a *n* × *n* matrix containing *n* vertices and where each entry *a _{ij}* represents the number of edges from vertex

*i*to vertex

*j*. To import your adjacency matrix, use the

`graph.adjacency()`

function.# producing a random adjacency matrix adj <- matrix(sample(0:1, 100, replace=T), 10, 10) # creating and plottig the graph from the adjacency matrix gr <- graph.adjacency(adj) plot(gr)

## ReferencesEdit

- Statnet website includes all the documentation on network analysis using R.
- Julien Barnier's introduction (in French)
- Journal of Statistical Software #24 Special Issue on Networks in R