simreg

A data set with simulated data from mixture regression models.

data

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

simreg function

A data frame with 1000 rows and 5 variables:<dl>
 <dt>yp</dt>
<dd>A dependent variable generated from a mixture 
 of a poisson regression with x</dd> <dt>yn</dt>
<dd>A dependent variable generated from a mixture 
 of a linear regression with x</dd> <dt>yc</dt>
<dd>A dependent variable generated from a mixture 
 of a linear regression with x and a concomitant variable of z</dd> <dt>x</dt>
<dd>An independent variable</dd> <dt>z</dt>
<dd>A concomitant variable</dd>
</dl>

Format

Simulated Regression Data — simreg

A data frame with 1000 rows and 5 variables:<dl>
 <dt>yp</dt>
<dd>A dependent variable generated from a mixture 
 of a poisson regression with x</dd>

 <dt>yn</dt>
<dd>A dependent variable generated from a mixture 
 of a linear regression with x</dd>

 <dt>yc</dt>
<dd>A dependent variable generated from a mixture 
 of a linear regression with x and a concomitant variable of z</dd>

 <dt>x</dt>
<dd>An independent variable</dd>

 <dt>z</dt>
<dd>A concomitant variable</dd>


</dl>

simreg: Simulated Regression Data

Description

Usage

Arguments

Format