vblpcmBIC function

calculate the BIC for the fitted VBLPCM object

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

Returns

The scalar value of the BIC

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.

Author(s)

Michael Salter-Townshend

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')