ergmm.par.object {latentnet}R Documentation

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:
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.

See Also

ergmm.par.list


[Package latentnet version 2.1-1 Index]