san {ergm} | R Documentation |
This function attempts to find a network or networks
whose statistics match those passed
in via the meanstats
vector.
## S3 method for class 'formula' san(object, nsim=1, seed=NULL, theta0=NULL, tau=1, invcov=NULL, burnin=10000, interval=10000, meanstats=NULL, basis=NULL, sequential=TRUE, constraints = ~., control = control.san(), verbose=FALSE, ...) ## S3 method for class 'ergm' san(object, nsim=1, seed=NULL, theta0=object$coef, burnin=10000, interval=10000, meanstats=NULL, basis=NULL, sequential=TRUE, constraints = NULL, control = control.san(), verbose=FALSE, ...)
object |
an R object. Either
a |
nsim |
Number of desired networks. |
seed |
Random number integer seed. |
theta0 |
Parameter values used for MCMC simulations. |
tau |
Currently unused. |
invcov |
Initial inverse covariance matrix used to calculate
Mahalanobis distance in determining how far a proposed MCMC move is from
the |
burnin |
Number of MCMC steps prior to recording first vector of network statistics. |
interval |
Number of MCMC steps between recordings of network statistics |
meanstats |
A vector of the same length as the number of terms implied by
the formula, which is either |
basis |
If not NULL, a network that forms the beginning of the Markov chain. If NULL, this is taken to be the network named in the formula. |
sequential |
Logical: Should the returned draws use the prior draw as the starting network or always use the initially passed network? |
constraints |
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
|
control |
A list of control parameters for algorithm
tuning. Constructed using |
verbose |
If this is |
... |
Further arguments passed to or used by methods. |
A network or list of networks that hopefully have network statistics close
to the meanstats
vector.