CODEWITHSUNDEEP
rnetwork-programminggraphigraph
Cantor_Set
Cantor_Set

Reputation: 101

R: Simulating ERGM model in R then generate adjacency matrix of that model

I use library(ergm) and library(igraph) and generate a ERGM network. But I want the adjacency matrix of that network. I am unable to find any function which can produce that.

library(ergm)
library(igraph)
g.use <- network(16,density=0.1,directed=FALSE)
#
# Starting from this network let's draw 3 realizations
# of a edges and 2-star network
#
g.sim <- simulate(~edges+kstar(2), nsim=3, coef=c(-1.8,0.03),
              basis=g.use, control=control.simulate(
                MCMC.burnin=1000,
                MCMC.interval=100))
#g.sim[[3]]
summary(g.sim)

Is it possible to find the adjacency matrix from g.sim? and how?

Upvotes: 0

Views: 156

Answers (1)

Onyambu
Onyambu

Reputation: 79328

EGRM package uses the network package and not the igraph package. You should maintain everythig in network and not load igraph as the two have some conflicting functions with same names.

In your case, you simulate 3 graphs thus you should have 3 adjacency matrices. The code is as below:

library(ergm)
g.use <- network(16,density=0.1,directed=FALSE)
g.sim <- simulate(~edges+kstar(2), nsim=3, coef=c(-1.8,0.03),
              basis=g.use, control=control.simulate(
                MCMC.burnin=1000,
                MCMC.interval=100))

The code you want:

lapply(g.sim, as.matrix)

[[1]]
   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1  0 0 0 0 1 0 0 0 0  0  0  0  0  0  0  0
2  0 0 0 0 0 1 0 1 0  0  0  0  0  1  0  0
3  0 0 0 1 1 0 1 0 0  0  0  0  1  0  0  1
4  0 0 1 0 0 0 0 0 1  0  0  0  0  0  0  0
5  1 0 1 0 0 0 0 0 0  0  0  0  1  1  0  0
6  0 1 0 0 0 0 0 0 0  1  0  0  0  0  0  0
7  0 0 1 0 0 0 0 0 0  0  1  0  0  0  0  1
8  0 1 0 0 0 0 0 0 0  1  1  1  1  0  1  0
9  0 0 0 1 0 0 0 0 0  0  0  0  0  0  0  1
10 0 0 0 0 0 1 0 1 0  0  0  0  1  0  0  0
11 0 0 0 0 0 0 1 1 0  0  0  0  1  0  0  0
12 0 0 0 0 0 0 0 1 0  0  0  0  0  0  0  0
13 0 0 1 0 1 0 0 1 0  1  1  0  0  0  0  1
14 0 1 0 0 1 0 0 0 0  0  0  0  0  0  0  0
15 0 0 0 0 0 0 0 1 0  0  0  0  0  0  0  0
16 0 0 1 0 0 0 1 0 1  0  0  0  1  0  0  0

[[2]]
   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1  0 0 0 0 0 0 0 0 0  0  0  1  1  0  0  0
2  0 0 0 0 0 0 0 0 0  0  1  0  0  0  0  0
3  0 0 0 1 0 0 0 0 0  0  1  0  0  0  1  0
4  0 0 1 0 0 0 0 0 0  0  0  0  0  0  0  0
5  0 0 0 0 0 0 1 0 0  0  0  0  0  0  0  1
6  0 0 0 0 0 0 0 1 1  0  1  1  1  0  0  1
7  0 0 0 0 1 0 0 0 0  0  1  0  0  0  0  0
8  0 0 0 0 0 1 0 0 0  0  0  0  0  0  1  0
9  0 0 0 0 0 1 0 0 0  0  0  1  0  0  0  0
10 0 0 0 0 0 0 0 0 0  0  0  0  1  1  0  0
11 0 1 1 0 0 1 1 0 0  0  0  0  0  0  0  0
12 1 0 0 0 0 1 0 0 1  0  0  0  0  0  0  1
13 1 0 0 0 0 1 0 0 0  1  0  0  0  0  0  0
14 0 0 0 0 0 0 0 0 0  1  0  0  0  0  0  0
15 0 0 1 0 0 0 0 1 0  0  0  0  0  0  0  0
16 0 0 0 0 1 1 0 0 0  0  0  1  0  0  0  0

[[3]]
   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1  0 0 0 0 0 0 0 0 0  0  0  0  1  0  0  1
2  0 0 0 0 0 1 0 0 0  0  0  1  1  0  0  0
3  0 0 0 0 1 0 0 0 0  1  1  0  0  0  1  0
4  0 0 0 0 0 0 0 0 0  0  0  0  1  0  0  0
5  0 0 1 0 0 0 0 0 0  0  0  0  0  0  0  0
6  0 1 0 0 0 0 1 0 1  0  0  0  1  0  1  0
7  0 0 0 0 0 1 0 0 0  0  0  0  0  1  1  0
8  0 0 0 0 0 0 0 0 0  0  0  0  0  0  0  0
9  0 0 0 0 0 1 0 0 0  0  0  0  0  0  0  0
10 0 0 1 0 0 0 0 0 0  0  0  0  0  0  1  1
11 0 0 1 0 0 0 0 0 0  0  0  0  0  0  0  1
12 0 1 0 0 0 0 0 0 0  0  0  0  1  1  1  0
13 1 1 0 1 0 1 0 0 0  0  0  1  0  0  0  0
14 0 0 0 0 0 0 1 0 0  0  0  1  0  0  0  0
15 0 0 1 0 0 1 1 0 0  1  0  1  0  0  0  1
16 1 0 0 0 0 0 0 0 0  1  1  0  0  0  1  0

Upvotes: 1

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