mstep.concomitant

This section was inspired by Flexmix.

A generic function for running the Expectation-Maximization (EM) algorithm
within a maximum likelihood framework, based on Dempster, Laird, and Rubin (1977) <doi:10.1111/j.2517-6161.1977.tb01600.x>
is implemented. It can be applied after a model fitting using R's existing functions and packages.

Dongjie Wu

Generic EM Algorithm

mstep.concomitant function

<dl><dt>formula</dt>
<dd>the formula of the concomitant model.</dd>
<dt>data</dt>
<dd>the data or model.frame related to the concomitant model.</dd>
<dt>postpr</dt>
<dd>the posterior probability matrix.</dd></dl>

Arguments

The mstep for the concomitant model. — mstep.concomitant

<dl>

<dt>formula</dt>
<dd>the formula of the concomitant model.</dd>


<dt>data</dt>
<dd>the data or model.frame related to the concomitant model.</dd>


<dt>postpr</dt>
<dd>the posterior probability matrix.</dd>

</dl>

mstep.concomitant: The mstep for the concomitant model.

Description

Usage

Value

Arguments