Information Criteria {EMCluster}  R Documentation 
These functions are tools for compute information criteria for the fitted models.
em.ic(x, emobj = NULL, pi = NULL, Mu = NULL, LTSigma = NULL,
llhdval = NULL)
em.aic(x, emobj = NULL, pi = NULL, Mu = NULL, LTSigma = NULL)
em.bic(x, emobj = NULL, pi = NULL, Mu = NULL, LTSigma = NULL)
em.clc(x, emobj = NULL, pi = NULL, Mu = NULL, LTSigma = NULL)
em.icl(x, emobj = NULL, pi = NULL, Mu = NULL, LTSigma = NULL)
em.icl.bic(x, emobj = NULL, pi = NULL, Mu = NULL, LTSigma = NULL)
x 
the data matrix, dimension 
emobj 
the desired model which is a list mainly contains 
pi 
the mixing proportion, length 
Mu 
the centers of clusters, dimension 
LTSigma 
the lower triangular matrices of dispersion,

llhdval 
the total log likelihood value of 
The em.ic
calls all other functions to compute AIC (em.aic
),
BIC (em.bic
), CLC (em.clc
), ICL (em.icl
), and
ICL.BIC (em.icl.bic
). All are useful information criteria for
model selections, mainly choosing number of cluster.
em.ic
returns a list containing all other information criteria
for given the data x
and the desired model emobj
.
WeiChen Chen wccsnow@gmail.com and Ranjan Maitra
https://www.stat.iastate.edu/people/ranjanmaitra
library(EMCluster, quietly = TRUE)
x2 < da2$da
emobj < list(pi = da2$pi, Mu = da2$Mu, LTSigma = da2$LTSigma)
em.ic(x2, emobj = emobj)