AIC.moc {moc} | R Documentation |
AIC.moc
generates a table of log-Likelihood, AIC, BIC ,
ICL-BIC and entropy values along with the degrees of freedom of multiple moc
objects.
logLik
returns on object of class logLik containing the
log-Likelihood,degrees of freedom and number of observations.
AIC(object,...,k=2) logLik(object,...)
object,... |
Objects of class moc . |
k |
can be any real number or the string "BIC". |
The computed value is -2*log-Likelihood + k*npar. Specific treatment is carried for BIC (k = log(nsubject*nvar)), AIC (k = 2) and log-Likelihood (k = 0). Setting k = "BIC", will produce a table with BIC, entropy = sum( wt * post * log(post) ) which is an indicator of mixture separation, df and ICL-BIC = BIC + 2 * entropy which is an entropy corrected BIC, see McLachlan, G. and Peel, D. (2000).
A data frame with the relevant information for one or more objects is returned .
Be aware that degrees of freedom (df) for mixture models are usually useless ( if not meaningless ) and likelihood-ratio of apparently nested models often doesn't converge to a Chi-Square with corresponding df.
Bernard Boulerice <Bernard.Boulerice@umontreal.ca>
McLachlan, G. and Peel, D. (2000) Finite mixture models,Wiley-Interscience, New York.