summary.em: Summaries of fitted finite mixture models using EM algorithm

In em: Generic EM Algorithm

Summaries of fitted finite mixture models using EM algorithm

Description

Summaries of fitted finite mixture models using EM algorithm

Usage

## S3 method for class 'em'
summary(object, ...)

Arguments

object	Output from em, representing a fitted model using EM algorithm.
...	other arguments used.

Value

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()'.

em documentation built on Jan. 11, 2023, 9:07 a.m.