graphon (version 0.3.2)

gmodel.block: Generate binary random graphs based on stochastic blockmodel

Description

Given a \((K\times K)\) stochastic blockmodel W, gmodel.block generates an (n-by-n) binary random graphs. All K blocks have same number of nodes, or almost identical if n is not a multiple of K. Parameter noloop controls whether generated observations have an edge from a node to itself, called a loop.

Usage

gmodel.block(W, n, rep = 1, noloop = TRUE)

Arguments

W

a \((K\times K)\) blockmodel matrix.

n

the number of nodes for each observation.

rep

the number of observations to be generated.

noloop

a logical value; TRUE for graphs without self-loops, FALSE otherwise.

Value

a named list containing

G

depending on rep value,

(rep=1)

an \((n\times n)\) observation, or

(rep>1)

a length-rep list where each element is an observation is an \((n\times n)\) realization from the model.

P

an \((n\times n)\) probability matrix of generating each edge.

See Also

gmodel.P

Examples

# NOT RUN {
## set inputs
W = matrix(c(0.9,0.2,0.2,0.7),nr=2)
n = 200

## generate 2 observations without self-loops.
out <- gmodel.block(W,n,rep=2,noloop=TRUE)

# }
# NOT RUN {
## Visualize generated graphs
par(mfrow=c(1,2), pty="s")
image(out$G[[1]]); title("Observation 1")
image(out$G[[2]]); title("Observation 2")
# }
# NOT RUN {
# }