| eval_dcsbm_loglr {nett} | R Documentation |
Log-likelihood ratio of two DCSBMs (fast with poi = TRUE)
Description
Computes the log-likelihood ratio of one DCSBM relative to another, using
estimated parameters B and theta based on the given label vectors.
Usage
eval_dcsbm_loglr(A, labels, poi = TRUE, eps = 1e-06)
Arguments
A |
adjacency matrix |
labels |
a matrix with two columns representing two different label vectors |
poi |
whether to use Poisson version of likelihood (instead of Bernoulli) |
eps |
truncation threshold for the Bernoulli likelihood, used when parameter phat is close to 1 or 0. |
Details
The log-likehood ratio is computed between two DCSBMs specified by the columns
of labels. The function computes the log-likelihood ratio of the model with
labels[ , 2] w.r.t. the model with labels[ , 1]. This is often used with two
label vectors fitted using different number of communities (say K and K+1).
When poi is set to TRUE, the function uses fast sparse matrix computations
and is scalable to large sparse networks.
Value
log-likelihood ratio
See Also
eval_dcsbm_like, eval_dcsbm_bic