ergmm.par.object {latentnet} | R Documentation |
A class ergmm.par
to represent a
parameter configuration for an exponential random graph
mixed model.
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:
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:
mlp : log p(Y,Z,β,μ,σ,delta,gamma,σ_delta,σ_gamma,|...) | 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|...) | Depending on the model, the log-probability or log-density of the network conditional on all the parameters. |
lpZ : log p(Z|μ,σ,K) | Log-density of latent space positions conditional on latent space or cluster parameters and cluster assignments. |
lpbeta : log p(β) | Prior log-density of the covariate coefficients. |
lpLV : log p(μ,σ) | 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. |