vblpcmBIC: calculate the BIC for the fitted VBLPCM object

In VBLPCM: Variational Bayes Latent Position Cluster Model for Networks

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')

VBLPCM documentation built on March 31, 2023, 9:21 p.m.