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我正在尝试在加权网络（network_ex）上运行指数随机图模型（ergm）。该网络显示了四个不同组中的个人之间的交互。组之间不能发生交互，因此需要在模型中包含块对角约束。但是，当我包含块对角线约束时，ergm 函数（否则运行）返回错误（见下文），我的 R 会话要么无限期运行，要么直接中止。

有没有办法基于加权块对角矩阵运行 ergm？

# load necessary packages
library(ergm)
library(ergm.count)

# create a toy example network to illustrate the issue presented  
VEC=c(0,0,5,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,4,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,4,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,2,4,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,1,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,1,2,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,2,0,0,2,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,4,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,4,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,2,2,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,6,2,4,4,2,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,1,5,0,1,2,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,1,0,3,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,2,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,2,0)
mat_ex=matrix(VEC,25,25)

nb=1:25
ID=rep("ID_",25)
names=paste0(ID,nb)
rownames(mat_ex)=names
colnames(mat_ex)=names

SeAg=c("F_Adult","F_Adult","M_Adult","M_Adult","M_Sub-Adult","F_Adult","M_Adult","F_Adult","M_Sub-Adult","M_Adult","F_Adult","M_Adult","M_Adult","M_Adult","F_Adult","F_Adult","F_Adult","F_Adult","F_Adult","M_Sub-Adult","M_Adult","M_Adult","M_Adult","F_Adult","M_Adult")
Group=c(1,1,1 ,1,1 ,2, 2, 2 ,2, 2, 2, 2, 3, 3, 3, 3, 3, 4 ,4 ,4, 4, 4, 4,4, 4)
network_ex=as.network(x = mat_ex,
                            directed = TRUE,
                            loops = FALSE,
                            matrix.type = "adjacency",
                            ignore.eval=FALSE,
                            names.eval='weight')
set.vertex.attribute(network_ex, "Sex_Age", as.character(SeAg))
set.vertex.attribute(network_ex, "Group", as.character(Group))

# run the ergm function with blockdiagonal constraint
ergm_ex <- ergm(network_ex~ 
                  sum
                +nodematch("Sex_Age",diff=TRUE,levels=c(1,2),form="sum")
                , response = 'weight'
                 , constraints = ~blockdiag("Group")
                , estimate = 'MLE'
                , reference = ~Poisson
                , control = control.ergm(MCMC.interval = 1000
                                         , MCMLE.maxit = 200
                                         , init.method = 'CD'
                                         , MCMC.samplesize = 1000
                                         , MCMC.prop.weights="random"
                                         , MCMC.burnin=100,seed=12345)
)

通过 CD-MCMLE 开始对比散度估计：迭代 1，最多 60 次：

根据 VEC 值，我还得到：

MH 提议功能的初始网络配置是不能提议任何切换的网络配置

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1 回答 1

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这似乎是一个错误。我已经在最新的开发版本中修复了它。这些可以通过访问https://github.com/statnet/ergm和https://github.com/statnet/ergm.count并使用 install_github() 或下载自述文件中的二进制文件来获得。另请注意，blockdiag() 约束已暂时移至https://github.com/statnet/tergm。

于 2021-03-23T02:11:20.763 回答