engineEdgeBayes function

Implementation of simulation engine for dynamic networks using smoothing estimates of change statistics.

engineEdgeBayes(
  start_network,
  inputcoeff,
  ns,
  model.terms,
  model.formula,
  graph_mode,
  group,
  intercept,
  exvar,
  maxlag,
  lagmat,
  ylag,
  lambda = NA,
  method = "bayesglm",
  alpha.glmnet,
  paramout = TRUE,
  Theta = NA
)

Arguments

• start_network: Initial list of networks
• inputcoeff: coefficient vector
• ns: number of time points for simulation
• model.terms: model terms in formula
• model.formula: model formula (ergm)
• graph_mode: 'digraph' by default
• group: group terms
• intercept: intercept terms
• exvar: extraneous covariates
• maxlag: maximum lag
• lagmat: lag matrix
• ylag: lag vector for network lag terms
• lambda: NA
• method: 'bayesglm' by default
• alpha.glmnet: NA
• paramout: T/F parameter estimation is returned.
• Theta: = prior probability matrix.

Examples

## Not run:

startNet <- rdNets[1:50]
model.terms=c("triadcensus.003", "triadcensus.012", "triadcensus.102", "triadcensus.021D", "gwesp")
model.formula = net~triadcensus(0:3)+gwesp(alpha=0, fixed=FALSE, cutoff=30)-1
graph_mode <- 'digraph'
group <- 'dnc'
alpha.glmnet <- 1
method <- 'bayesglm'
maxlag <- 3
lambda <- NA
intercept <- "edges"
cdim <- length(model.terms)
lagmat <- matrix(sample(c(0,1),(maxlag+1)*cdim,replace = TRUE),ncol = cdim)
ylag <- rep(1,maxlag)
lagmat[1,] <- rep(0,ncol(lagmat))

out.coef <- paramEdge(input_network = startNet,
                model.terms = model.terms,
                model.formula = model.formula,
                graph_mode='digraph',
                group=group,intercept = intercept,
                exvar=NA,
                maxlag = maxlag,
                lagmat = lagmat,
                ylag = ylag,
                lambda = NA, method='bayesglm',
                alpha.glmnet=1)

inputcoeff <- out.coef$coef$coef.edge
nvertex <- 47 ##find vertex here
ns <- 1
exvar <- NA
for(i in seq_along(startNet)) Theta <- Theta + startNet[[i]][,]
Theta <- Theta/length(startNet)
Theta <- thresh(Theta)
out.bayes <- engineEdgeBayes(start_network=startNet,
inputcoeff=inputcoeff,
ns=ns,
model.terms=model.terms,
model.formula=model.formula,
graph_mode=graph_mode,
group=group,intercept=intercept,
exvar=exvar,
maxlag=maxlag,
lagmat=lagmat,
ylag=ylag,
lambda = NA, method='bayesglm',
alpha.glmnet=alpha.glmnet,
Theta = Theta)
## End(Not run)