nVarParams

Gives the number of variance parameters for parameterizations of the 
 Gaussian mixture model that are used in MCLUST.

cluster

Gaussian finite mixture models fitted via EM algorithm for
model-based clustering, classification, and density estimation,
including Bayesian regularization, dimension reduction for
visualisation, and resampling-based inference.

Luca Scrucca

mclust

Gaussian Mixture Modelling for Model-Based Clustering,
Classification, and Density Estimation

Chris Fraley

Adrian E. Raftery

Thomas Brendan Murphy

Michael Fop

nVarParams function

<dl> <dt>modelName</dt>
<dd>A character string indicating the model. The help file for
 <code>mclustModelNames</code> describes the available models.</dd> <dt>d</dt>
<dd>The dimension of the data. Not used for models in which neither
 the shape nor the orientation varies.</dd> <dt>G</dt>
<dd>The number of components in the Gaussian mixture model used to compute
 <code>loglik</code>.</dd> <dt>... </dt>
<dd>Catches unused arguments in indirect or list calls via <code>do.call</code>.</dd></dl>

Arguments

Number of Variance Parameters in Gaussian Mixture Models — nVarParams

<dl>

 <dt>modelName</dt>
<dd>A character string indicating the model. The help file for
 <code>mclustModelNames</code> describes the available models.</dd>

 <dt>d</dt>
<dd>The dimension of the data. Not used for models in which neither
 the shape nor the orientation varies.</dd>

 <dt>G</dt>
<dd>The number of components in the Gaussian mixture model used to compute
 <code>loglik</code>.</dd>

 <dt>... </dt>
<dd>Catches unused arguments in indirect or list calls via <code>do.call</code>.</dd>

</dl>

nVarParams: Number of Variance Parameters in Gaussian Mixture Models

Description

Usage

Value

Arguments

Details

See Also

Examples