engineVertex: Simulation Engine for dynamic Vertex case.

In SSDALab/dnr: Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family

Description

Simulation engine for dynamic networks with variable number of vertices. Implements exponential family based hierarchical model for vertices and the edges.

Usage

engineVertex(
  InputNetwork,
  numSim,
  maxLag,
  VertexStatsvec = rep(1, nvertexstats),
  VertexLag = rep(1, maxLag),
  VertexLagMatrix = matrix(1, maxLag, length(VertexStatsvec)),
  VertexModelGroup = NA,
  VertexAttLag = rep(1, maxLag),
  dayClassObserved = NA,
  dayClassFuture = NA,
  EdgeModelTerms,
  EdgeModelFormula,
  EdgeGroup = NA,
  EdgeIntercept = c("edges"),
  EdgeNetparam = NA,
  EdgeExvar = NA,
  EdgeLag = rep(1, maxLag),
  EdgeLagMatrix = matrix(1, maxLag, length(EdgeModelTerms)),
  regMethod = "bayesglm",
  paramout = TRUE
)

Arguments

InputNetwork	List of input networks
numSim	number of time points to simulate
maxLag	maximum Lag
VertexStatsvec	Binary vector for vertex model.
VertexLag	vector of lag for vertex
VertexLagMatrix	matrix of lags for vertex stats.
VertexModelGroup	Group term for vertex model.
VertexAttLag	Lag vector for group term for vertex.
dayClassObserved	Observed day class.
dayClassFuture	Dayclass vector for future, must be of size numsim.
EdgeModelTerms	Edge Model terms
EdgeModelFormula	Edge model formula
EdgeGroup	edge group term
EdgeIntercept	edge intercept
EdgeNetparam	edge network parameter name
EdgeExvar	edge extraneous variable
EdgeLag	edge Lag vector
EdgeLagMatrix	edge lag matrix
regMethod	regression method. "bayesglm" by default
paramout	T/F on if regression needs to run.

Value

List with following elements: SimNetwork: Output Networks EdgeParameterMat: Matrix of edge parameter VertexParameterMat: Matrix of Vertex parameters.

Author(s)

Abhirup

Examples

## Not run: 
nvertexstats <- 9
maxLag = 3
VertexLag = rep(1, maxLag)
VertexLagMatrix <- matrix(0, maxLag, nvertexstats)
VertexLagMatrix[, c(4, 7)] <- 1
VertexLagMatrix[c(2,3),7] <- 0

getWeekend <- function(z){
    weekends <- c("Saturday", "Sunday")
    if(!network::is.network(z)){
        if(is.na(z)) return(NA)
    } else {
         zDay <- get.network.attribute(z, attrname = "day")
         out <- ifelse(zDay %in% weekends, 1, 0)
         return(out)   
    }
}

dayClass <- numeric(length(beach))
for(i in seq_along(dayClass)) {
    dayClass[i] <- getWeekend(beach[[i]])
}
dayClass <- na.omit(dayClass)
simResult <- suppressWarnings(engineVertex(InputNetwork = beach,
                          numSim = 5,
                          maxLag = 3,
                          VertexStatsvec = rep(1, nvertexstats),
                          VertexModelGroup = "regular",
                          VertexAttLag = rep(1, maxLag),
                          VertexLag = rep(1, maxLag),
                          VertexLagMatrix = VertexLagMatrix,
                          dayClassObserved = dayClass,
                          dayClassFuture = c(1, 0, 0, 0, 0),
                          EdgeModelTerms = NA,
                          EdgeModelFormula = NA,
                          EdgeGroup = NA,
                          EdgeIntercept = c("edges"),
                          EdgeNetparam = c("logSize"),
                          EdgeExvar = NA,
                          EdgeLag = c(0, 1, 0),
                          paramout = TRUE
                          ))
## End(Not run)

SSDALab/dnr documentation built on Dec. 28, 2020, 8:02 a.m.