Compute the log-likelihood of a
"TopicModel" object. For "VEM" objects the sum of
the log-likelihood of all documents given the parameters for the
topic distribution and for the word distribution of each topic is
approximated using the variational parameters and underestimates
the log-likelihood by the Kullback-Leibler divergence between the
variational posterior probability and the true posterior
probability.
object = Gibbs_list:
Compute the log-likelihoods of the
"TopicModel" objects contained in the "Gibbs_list"
object.
providing 
.