AIC.moc {moc}R Documentation

Information Criterion for MOC models

Description

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.

Usage


       AIC(object,...,k=2)

       logLik(object,...)

Arguments

object,... Objects of class moc.
k can be any real number or the string "BIC".

Details

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).

Value

A data frame with the relevant information for one or more objects is returned .

Note

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.

Author(s)

Bernard Boulerice <Bernard.Boulerice@umontreal.ca>

References

McLachlan, G. and Peel, D. (2000) Finite mixture models,Wiley-Interscience, New York.

See Also

moc


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