FLXnested-class

coerce,list,FLXnested-method

coerce,NULL,FLXnested-method

coerce,numeric,FLXnested-method

initialize,FLXnested-method

Specification of nesting structure for regression coefficients.

classes

A general framework for finite mixtures of regression
models using the EM algorithm is implemented. The E-step and all
data handling are provided, while the M-step can be supplied by the
user to easily define new models. Existing drivers implement
mixtures of standard linear models, generalized linear models and
model-based clustering.

Bettina Gruen

flexmix

Flexible Mixture Modeling

Friedrich Leisch

Deepayan Sarkar

Frederic Mortier

Nicolas Picard

FLXnested-class function

Objects can be created by calls of the form <code>new("FLXnested",
 formula, k, ...)</code>. In addition, named lists can be coerced to
<code>FLXnested</code> objects, names are completed if unique.

Objects from the Class

<dl>
 <dt><code>formula</code>:</dt>
<dd>Object of class <code>"list"</code> containing the
 formula for determining the model matrix for each nested parameter.</dd> <dt><code>k</code>:</dt>
<dd>Object of class <code>"numeric"</code> specifying the
 number of components in each group.</dd> 
</dl>

Slots

Friedrich Leisch and Bettina Gruen

Author

Class "FLXnested" — FLXnested-class

<dl>
 <dt><code>formula</code>:</dt>
<dd>Object of class <code>"list"</code> containing the
 formula for determining the model matrix for each nested parameter.</dd>

 <dt><code>k</code>:</dt>
<dd>Object of class <code>"numeric"</code> specifying the
 number of components in each group.</dd>

 
</dl>

FLXnested-class: Class "FLXnested"

Description

Arguments

Objects from the Class

Slots

Author