density

This function computes densities of 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 

density function

<dl><dt>gmm</dt>
<dd>An object of class <code>gmm</code>.</dd>
<dt>data</dt>
<dd>A data frame or numeric matrix containing the observations whose
densities are computed. Its columns must explicitly be named after the
variables of <code>gmm</code>.</dd>
<dt>y</dt>
<dd>A character vector containing the dependent variables if conditional
densities are computed. If <code>NULL</code> (the default), joint densities are
computed.</dd>
<dt>log</dt>
<dd>A logical value indicating whether the densities are returned as
log-densities.</dd></dl>

Arguments

Compute densities of a Gaussian mixture model — density

<dl>

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


<dt>data</dt>
<dd>A data frame or numeric matrix containing the observations whose
densities are computed. Its columns must explicitly be named after the
variables of <code>gmm</code>.</dd>


<dt>y</dt>
<dd>A character vector containing the dependent variables if conditional
densities are computed. If <code>NULL</code> (the default), joint densities are
computed.</dd>


<dt>log</dt>
<dd>A logical value indicating whether the densities are returned as
log-densities.</dd>

</dl>

density: Compute densities of a Gaussian mixture model

Description

Usage

Value

Arguments

See Also

Examples