em {em}

A Generic EM Algorithm

Description

This is a generic EM algorithm that can work on specific models/objects. Currently, it supports 'lm', 'glm', 'gnm' in package gnm, 'clogit' in package survival and 'multinom' in package nnet. Use '?em.default' to check the manual of the default function of 'em'.

Usage

em(object, ...)

Arguments

object

the model used, e.g. 'lm', 'glm', 'gnm', 'clogit', 'multinom'

...

arguments used in the 'model'.

Value

An object of class 'em' is a list containing at least the following components: models a list of models/objects whose class are determined by a model fitting from the previous step. pi the prior probabilities. latent number of the latent classes. algorithm the algorithm used (could be either 'em', 'sem' or 'cem'). obs the number of observations. post_pr the posterior probabilities. concomitant a list of the concomitant model. It is empty if no concomitant model is used. init.method the initialization method used. call the matched call. terms the codeterms object used.

Author(s)

Dongjie Wu

Examples

fit.lm <- lm(yn ~ x, data = simreg)
results <- em(fit.lm, latent = 2, verbose = FALSE) 
fmm_fit <- predict(results)
fmm_fit_post <- predict(results, prob = "posterior")