R：在 R 中模拟 ERGM model 然后生成该 Z20F3CZ3E630DAF3994D8CZ 的邻接矩阵

Question

我使用library(ergm)和library(igraph)并生成一个 ERGM 网络。 但我想要那个网络的邻接矩阵。 我找不到任何可以生产的 function。

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)
 

是否可以从g.sim找到邻接矩阵？ 如何？

Answer 1

EGRM package 使用network package 而不是igraph package。 您应该维护network中的所有内容，而不是加载igraph ，因为两者具有一些具有相同名称的冲突功能。

在您的情况下，您模拟 3 个图，因此您应该有 3 个邻接矩阵。 代码如下：

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))

你想要的代码：

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