ergmm.par.object: An ERGMM Parameter Configuration
Description
A class ergmm.par to represent a
parameter configuration for an exponential random graph
mixed model.Details
An ergmm.par object is essentially a named list of parameter
values. It can be accessed in much the same way a list can, but no
partial matching is performed.
The structure of ergmm.par is a list which may include some of the following:
ll{
beta Numeric vector of covariate coefficients.
Z.K Integer vector of cluster assignments.
Z.mean Numeric matrix with rows being cluster means.
Z.var Depending on the model, either a numeric vector with
within-cluster variances or a numeric scalar with the overal latent space variance.
Z.pK Numeric vector of probabilities of a vertex being
in a particular cluster.
Z Numeric matrix with rows being latent space positions.
}
In some cases (such as when representing MCMC or optimization output),
the object may also have some of the following:
ll{
mlp: $\log
p(Y,Z,\beta,\mu,\sigma,\delta,\gamma,\sigma_\delta,\sigma_\gamma,|\dots)$ Joint
probability/density of network, the covariate coefficients, the
latent space positions and parameters, and the random effects and
their variances, conditional on cluster assignments.
llk: $\log p(Y|\dots)$ Depending on the model, the log-probability or
log-density of the network conditional on all the parameters.
lpZ: $\log p(Z|\mu,\sigma,K)$ Log-density of latent space positions conditional on
latent space or cluster parameters and cluster assignments.
lpbeta: $\log p(\beta)$ Prior log-density of the covariate coefficients.
lpLV: $\log p(\mu,\sigma)$ Prior log-density of latent space or cluster
parameters (but not that of the cluster assignments).
Z.rate Proportion of single-vertex proposals accepted over the preceding
interval.
beta.rate Proportion of group proposals accepted over the preceding interval.
}