plot.matrixseries

Visualise convergence properties of vocalisation graphs

Create adjacency matrices of vocalisation graphs from
dataframes containing sequences of speech and silence intervals,
transforming these matrices into Markov diagrams, and generating
datasets for classification of these diagrams by 'flattening' them
and adding global properties (functionals) etc. Vocalisation
diagrams date back to early work in psychiatry (Jaffe and Feldstein,
1970) and social psychology (Dabbs and Ruback, 1987) but have only
recently been employed as a data representation method for machine
learning tasks including meeting segmentation (Luz, 2012)
<doi:10.1145/2328967.2328970> and classification (Luz,
2013) <doi:10.1145/2522848.2533788>.

Saturnino Luz

vocaldia

Create and Manipulate Vocalisation Diagrams

plot.matrixseries function

<dl><dt>x</dt>
<dd>an object of class matrixseries; a list where the
\(i^{th}\) element corresponds to \(M^i\).</dd>
<dt>...</dt>
<dd>extra graphics parameters for plot.</dd>
<dt>par</dt>
<dd>graphic parameters alist</dd>
<dt>interact</dt>
<dd>if TRUE, pauses the drawing after each node.</dd></dl>

Arguments

plotConvergence: plots Markov diagram convergence. — plot.matrixseries

<dl>

<dt>x</dt>
<dd>an object of class matrixseries; a list where the
\(i^{th}\) element corresponds to \(M^i\).</dd>


<dt>...</dt>
<dd>extra graphics parameters for plot.</dd>


<dt>par</dt>
<dd>graphic parameters alist</dd>


<dt>interact</dt>
<dd>if TRUE, pauses the drawing after each node.</dd>

</dl>

plot.matrixseries: plotConvergence: plots Markov diagram convergence.

Description

Usage

Value

Arguments

Details

Examples