This function calculates Bayes factors to evaluate evidence in favor of
clustering for models fitted with the bgms package (i.e., with arguments
package = "bgms" and edge_prior = "Stochastic-Block" within
the easybgm function). The function supports two types of Bayes factors:
Bayes factors between two point hypothesized number of clusters (b1 and b2),
and Bayes factor of the hypothesis of clustering (i.e., the complement hypothesis)
against the hypothesis of no clustering (i.e., the null, which simply means
that the network exibits one global cluster).
clusterBayesfactor(fit, type = "complement", b1 = NULL, b2 = NULL)A numeric value representing the Bayes factor. When type is "point",
the Bayes factor represents evidence in favor of b1 clusters against b2
clusters. When type is "complement", the Bayes factor represents evidence
in favor of clustering (i.e., more than one cluster) against no clustering.
A fitted object of class easybgm or bgms containing
the clustering results.
A character string specifying the type of Bayes factor to calculate.
Options are "point" or "complement". Defaults to "complement".
Indicates the number of clusters according to the first point hypothesis,
required for type = "point".
Indicates the number of clusters according to the second point hypothesis,
required for type = "point".