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