Description Usage Arguments Value Author(s) References Examples
Estimate the maximum likelihood estimators for P and delta at each time point in the list of adjacency matrices
1 | MLE.DCSBM(Adjacency.list, community.array, T, k)
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Adjacency.list: |
list of adjacency matrices in the observed dynamic network |
community.array: |
an array of length T whose tth entry is a numeric vector of length n specifying community labels at time t |
T: |
number of graphs in the temporal sequence |
k: |
number of communities (fixed accross time) Note, this is the pre-conceived idea of how many communities there are. |
a list containing the objects
P.hat.array: an array of length T whose tth entry is the estimated MLE of P for the tth network
delta.hat.array: an array of length T whose tth entry are the estimated MLEs of the delta parameters for the tth network
delta.hat.global: a numeric of length T whose tth entry is the estimated MLE of the overall standard deviation of the theta parameters for the tth network
James D. Wilson and Nathaniel T. Stevens
Wilson, James D., Stevens, Nathaniel T., and Woodall, William H. (2016). <e2><80><9c>Modeling and estimating change in temporal networks via a dynamic degree corrected stochastic block model.<e2><80><9d> arXiv Preprint: http://arxiv.org/abs/1605.04049
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | #Generate a collection of 50 networks with a change at time 25. The change is a local
#change in connection propensity in community 1
n <- 100
P.old <- cbind(c(0.10, 0.01), c(0.02, 0.075))
P.new <- cbind(c(0.20, 0.025), c(0.02, 0.075))
P.array <- array(c(replicate(25, P.old), replicate(25, P.new)), dim = c(2, 2, 50))
community.array <- array(rep(c(rep(1, 50), rep(2, 50)), 50), dim = c(1, 100, 50))
delta.array <- array(rep(rep(0.2, 2), 50), dim = c(1, 2, 50))
dynamic.net <- dynamic.DCSBM(n = 100, T = 50, P.array = P.array,
community.array = community.array,
delta.array = delta.array, edge.list = FALSE)
image(Matrix(dynamic.net$Adjacency.list[[1]]))
image(Matrix(dynamic.net$Adjacency.list[[30]]))
#Estimate the MLEs
MLEs.example <- MLE.DCSBM(dynamic.net$Adjacency.list, community.array = community.array,
T = 50, k = 2)
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