This function attempts to find a network or networks
whose statistics match those passed
in via the target.stats
vector.
# S3 method for formula
san(object,
response=NULL,
reference=~Bernoulli,
constraints=~.,
target.stats=NULL,
nsim=1,
basis=NULL,
sequential=TRUE,
control=control.san(),
verbose=FALSE,
…)
# S3 method for ergm
san(object,
formula=object$formula,
constraints=object$constraints,
target.stats=object$target.stats,
nsim=1,
basis=NULL,
sequential=TRUE,
control=object$control$SAN.control,
verbose=FALSE,
…)
Either
a formula
or an ergm
object.
The formula
should be of the form y ~ <model terms>
,
where y
is a network object or a matrix that can be
coerced to a network
object. For the details
on the possible
<model terms>
, see ergm-terms
. To create a
network
object in R, use the
network()
function,
then add nodal attributes to it using the %v%
operator if necessary.
EXPERIMENTAL. Name of the edge attribute whose value is to be
modeled. Defaults to NULL
for simple presence or absence.
EXPERIMENTAL. One-sided formula whose RHS
gives the reference measure to
be used. (Defaults to ~Bernoulli
.)
(By default, the formula
is taken from the ergm
object.
If a different formula
object is wanted, specify it here.
A one-sided formula specifying one or more constraints
on the support of the distribution of the networks being
simulated. See the documentation for a similar argument for
ergm
and see list of
implemented constraints for more information. For
simulate.formula
, defaults to no constraints. For
simulate.ergm
, defaults to using the same constraints as
those with which object
was fitted.
A vector of the same length as the number of terms
implied by the formula, which is either object
itself in the
case of san.formula
or object$formula
in the case
of san.ergm
.
Number of desired networks.
If not NULL, a network
object used to start
the Markov chain. If NULL, this is taken to be the network named
in the formula.
Logical: If TRUE, the returned draws always use the prior draw as the starting network; if FALSE, they always use the original network.
A list of control parameters for algorithm
tuning; see control.san
.
Logical: If TRUE, print out more detailed information as the simulation runs.
Further arguments passed to other functions.
A network or list of networks that hopefully have network statistics close
to the target.stats
vector.