vblpcmbic {VBLPCM} | R Documentation |
calculate the BIC for the fitted VBLPCM object
Description
calculate the BIC for the fitted VBLPCM object
Usage
vblpcmbic(v.params)
Arguments
v.params |
The fitted values; output from vblpcmfit() |
Details
BIC = BIC(edges | positions) + BIC(positions | clusters) w/ BIC(edges | positions) = -2 loglikelihood + (P+1)log(number of edges) and BIC(positions | clusters) as per mclust
Value
The scalar value of the BIC
Author(s)
Michael Salter-Townshend
References
Mark S. Handcock, Adrian E. Raftery and Jeremy Tantrum (2007). "Model-Based Clustering for Social Networks." Journal of the Royal Statistical Society: Series A (Statistics in Society), 170(2), 301-354.
See Also
latentnet::summary.ergmm
Examples
data(sampson)
set.seed(1)
### plot the BIC for G=2,3,4 groups
gbic<-list(groups=NULL,bic=NULL)
for (g in 2:4)
{
v.fit<-vblpcmfit(vblpcmstart(samplike,G=g,LSTEPS=1e3),STEPS=20)
gbic$groups[g]=v.fit$G
gbic$bic[g]=v.fit$BIC$overall
}
plot(gbic$groups, gbic$bic, main="BIC results", xlab="# groups", ylab="BIC", t='b')
[Package VBLPCM version 2.4.9 Index]