npars_clustMD

internal

Model-based clustering of mixed data (i.e. data which consist of
continuous, binary, ordinal or nominal variables) using a parsimonious
mixture of latent Gaussian variable models.

Damien McParland

clustMD

Model Based Clustering for Mixed Data

Isobel Claire Gormley

npars_clustMD function

<dl><dt>model</dt>
<dd>the <code>clustMD</code> covariance model fitted.</dd>
<dt>D</dt>
<dd>the dimension of the latent data.</dd>
<dt>G</dt>
<dd>the number of mixture components.</dd>
<dt>J</dt>
<dd>the number of variables.</dd>
<dt>CnsIndx</dt>
<dd>the number of continuous variables.</dd>
<dt>OrdIndx</dt>
<dd>the sum of the number of continuous and ordinal (including
binary) variables.</dd>
<dt>K</dt>
<dd>a vector indicating the number of levels of each categorical 
variable.</dd></dl>

Arguments

Calculates the number of free parameters for the clustMD model. — npars_clustMD

<dl>

<dt>model</dt>
<dd>the <code>clustMD</code> covariance model fitted.</dd>


<dt>D</dt>
<dd>the dimension of the latent data.</dd>


<dt>G</dt>
<dd>the number of mixture components.</dd>


<dt>J</dt>
<dd>the number of variables.</dd>


<dt>CnsIndx</dt>
<dd>the number of continuous variables.</dd>


<dt>OrdIndx</dt>
<dd>the sum of the number of continuous and ordinal (including
binary) variables.</dd>


<dt>K</dt>
<dd>a vector indicating the number of levels of each categorical 
variable.</dd>

</dl>

npars_clustMD: Calculates the number of free parameters for the `clustMD` model.

Description

Usage

Value

Arguments

See Also