remove_var

This function removes variables from a Gaussian mixture model.

Gaussian mixture graphical models include Bayesian networks and
dynamic Bayesian networks (their temporal extension) whose local probability
distributions are described by Gaussian mixture models. They are powerful
tools for graphically and quantitatively representing nonlinear dependencies
between continuous variables. This package provides a complete framework to
create, manipulate, learn the structure and the parameters, and perform
inference in these models. Most of the algorithms are described in the PhD
thesis of Roos (2018) <https://tel.archives-ouvertes.fr/tel-01943718>.

J<c3><a9>r<c3><a9>my Roos

gmgm

Gaussian Mixture Graphical Model Learning and Inference

Jérémy Roos

RATP Group 

remove_var function

<dl><dt>gmm</dt>
<dd>An object of class <code>gmm</code>.</dd>
<dt>var</dt>
<dd>A character vector containing the removed variables.</dd></dl>

Arguments

Remove variables from a Gaussian mixture model — remove_var

<dl>

<dt>gmm</dt>
<dd>An object of class <code>gmm</code>.</dd>


<dt>var</dt>
<dd>A character vector containing the removed variables.</dd>

</dl>

remove_var: Remove variables from a Gaussian mixture model

Description

Usage

Value

Arguments

See Also

Examples