| rergm {latentnetHRT} | R Documentation |
rergm is used to draw from exponential family random network
models in their natural parameterizations.
See ergmm for more information on these models.
rergm(object, ...)
## Default S3 method:
rergm(object,...,prob,theta0,n=1,
directed=TRUE,numedges=NULL)
## S3 method for class 'ergmm':
rergm(object, mkl = TRUE, n = 1, ...)
object |
an R object. Either a number of nodes in the network,
a formula or an ergmm object. See documentation for ergmm.
If the number of nodes in the network is given then
Bernoulli networks are drawn. |
prob |
The probability of a link for Bernoulli networks. Defaults to 0.5 if neither prob nor theta0 are given. |
theta0 |
For Bernoulli networks this is the log-odds of a tie, however it is only used if prob is not specified. |
directed |
Whether the Bernoulli network should be directed or undirected. |
numedges |
If present, sample the network(s) conditional on this number of edges (rather than independently with the specified probability). |
n |
Size of the sample of networks to be randomly drawn from the given distribution on the set of all networks, returned by the Metropolis-Hastings algorithm. |
mkl |
If this is TRUE, we will use the minimum Kullback-Leibler positions as the basis of the simulation (rather than the default MLE positions). |
... |
further arguments passed to or used by methods. |
A sample of networks is randomly drawn from the specified model. The
model is either specified by the first argument of the function. If
the first argument is a an ergmm object
then this defines the model.
If this is not given as the
first argument then a Bernoulli network is generated with the probability
of ties defined by prob or theta0.
Note that the first network is sampled after burnin + interval
steps, and any subsequent networks are sampled each
interval steps after the first.
More information can be found by looking at the documentation of
ergmm.
rergm returns an object of class network.series that is a list
consisting of the following elements:
formula |
The formula used to generate the sample. |
networks |
A list of the generated networks. |
stats |
The ntimes p matrix of network change statistics, where n is the sample size and p is the number of network change statistics specified in the model. |
ergmm, network, print.network
# # Let's draw from a Bernoulli model with 16 nodes # and tie probability 0.1 # g.use <- rergm(16,prob=0.1,directed=FALSE) # data(sampson) gest <- ergmm(samplike ~ latent(k=2)) summary(gest) # # Draw from the fitted model # g.sim <- rergm(gest,n=100,burnin=1000,interval=1000) g.sim