plot.silhouette.ct

Plots the silhouette index, generated by a call to
<code>silhouette.ct</code>, for a continuous-time k-means clustering object.

Implements a basis function or functional data analysis framework
for several techniques of multivariate analysis in continuous-time
setting. Specifically, we introduced continuous-time analogues of
several classical techniques of multivariate analysis, such as
principal component analysis, canonical correlation analysis,
Fisher linear discriminant analysis, K-means clustering, and so
on. Details are in Biplab Paul, Philip T. Reiss, Erjia Cui and Noemi Foa (2025)
"Continuous-time multivariate analysis" <doi: 10.1080/10618600.2024.2374570>.

Biplab Paul

ctmva

Continuous-Time Multivariate Analysis

Philip Tzvi Reiss

Noemi Foa

Dror Arbiv

plot.silhouette.ct function

<dl><dt>x</dt>
<dd>silhouette object produced by <code>silhouette.ct</code></dd>
<dt>mark.transitions</dt>
<dd>logical: Should transitions between clusters be marked
with vertical lines? Defaults to <code>TRUE</code>.</dd>
<dt>xlab, ylab</dt>
<dd>x- and y-axis labels</dd>
<dt>...</dt>
<dd>other arguments passed to <code><a href="/link/plot?package=ctmva&version=1.6.0" data-mini-rdoc="ctmva::plot">plot</a></code></dd></dl>

Arguments

Philip Tzvi Reiss &lt;reiss@stat.haifa.ac.il&gt;

Author

Plot a silhouette.ct object — plot.silhouette.ct

<dl>

<dt>x</dt>
<dd>silhouette object produced by <code>silhouette.ct</code></dd>


<dt>mark.transitions</dt>
<dd>logical: Should transitions between clusters be marked
with vertical lines? Defaults to <code>TRUE</code>.</dd>


<dt>xlab, ylab</dt>
<dd>x- and y-axis labels</dd>


<dt>...</dt>
<dd>other arguments passed to <code><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></code></dd>

</dl>

plot.silhouette.ct: Plot a silhouette.ct object

Description

Usage

Value

Arguments

Author

See Also