ergmm.par.list | R Documentation |
A class ergmm.par.list
to represent a
series of parameter configurations for the same exponential random graph
mixed model.
as.ergmm.par.list(x, ...) ## S3 method for class 'ergmm.par.list' x[i] ## S3 method for class 'ergmm.par.list' length(x) ## S3 method for class 'ergmm.par.list' x[[i]] ## S3 method for class 'ergmm.par.list' unstack(x, ...)
x |
an |
... |
extra arguments, currently unused. |
i |
index of the iteration to extract. |
[[
operator with a
numeric or integer index returns a
list with the the
configuration with that index. [
operator given a numeric
vector returns a ergmm.par.list
object with the subset of
configurations with the indices given.
The structure of ergmm.par.list
is derived from named lists, with each entry having an
additional dimension (always the first one), indexed by
configuration. That is, scalars become vectors, vectors become
matrixes with the original vectors in rows, and matrixes become
3-dimensional arrays, with the original matrixes indexed by their
first dimension. See terms.ergmm
for comon elements of
these configurations.
In some cases, such as when representing MCMC or optimization output,
the object may also have some of the following elements:
mlp
\log p(Y,Z,β,μ,σ,δ,γ,σ_δ,σ_γ,|K), the 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.
lpY
\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), the log-density of latent space positions conditional on latent space or cluster parameters and cluster assignments.
lpbeta
\log p(β), the prior log-density of the covariate coefficients.
lpRE
\log p(δ,γ|σ_δ,σ_γ), the log-density of all random effects, conditional on their respective variances.
lpLV
\log p(μ,σ), the prior log-density of latent space or cluster parameters (but not that of the cluster assignments).
lpREV
\log p(σ_δ,σ_γ), the prior log-density of all random effect variances.
Z.rate
Proportion of single-vertex proposals accepted over the preceding interval.
beta.rate
Proportion of group proposals accepted over the preceding interval.
ergmm