Summaries of fitted finite mixture models using EM algorithm
# S3 method for em
summary(object, ...)An object of class `summary.em` is a list containing at least the following components:
call the matched call.
coefficients
pi the prior probabilities.
latent number of the latent classes.
ll log-likelihood value.
sum.models summaries of models generated by `summary()` of models from each class.
df degree of freedom.
obs number of observations.
AIC the Akaike information criterion.
BIC the Bayesian information criterion.
concomitant a list of the concomitant model. It is empty if no concomitant model is used.
concomitant.summary summaries of the concomitant model generated by `summary()`.
Output from em, representing a fitted model using EM algorithm.
other arguments used.