sstep

Given the posterior probability, generate a matrix to assign
each individual to a class. The assignment is randomly sampled based on the posterior probability.

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

sstep function

<dl><dt>postpr</dt>
<dd>(`matrix()`) 
The matrix of the posterior probability</dd></dl>

Arguments

S-step of EM algorithm — sstep

<dl>

<dt>postpr</dt>
<dd>(`matrix()`) 
The matrix of the posterior probability</dd>

</dl>

sstep: S-step of EM algorithm

Description

Usage

Arguments