control.san(coef=NULL, SAN.tau=1,
SAN.invcov=NULL,
SAN.burnin=100000,
SAN.interval=10000,
SAN.init.maxedges=20000,
SAN.prop.weights="default",
SAN.prop.args=list(),
SAN.packagenames=c(),
MPLE.samplesize = 50000,
network.output="network",
seed=NULL,
parallel=0,
parallel.type=NULL,
parallel.version.check=TRUE)
target.stats vector.
If NULL, taken to be the covariance
matrix returned when fitting the MPLE"default", which picks a
reasonable default for the specified constraint.
Other possible values are
"TNT", "random"set.seed"MPI" and
"SOCK". Defaults to using the snow package
default.ergm running on the slave nodes is the
same as that running on the master node.san function.
See the usage section in san for details.san