Silhouette.coefficient

Silhouette coefficients given a dendrogram

internal

Directed Dependence Coefficient (didec) is a measure of functional dependence.
Multivariate Feature Ordering by Conditional Independence (MFOCI) is a variable selection
algorithm based on didec.
Hierarchical Variable Clustering (VarClustPartition) is a variable clustering method
based on didec.
For more information, see the paper by Ansari and Fuchs
(2025, <doi:10.48550/arXiv.2212.01621>), and the paper by Fuchs and Wang
(2024, <doi:10.1016/j.ijar.2024.109185>).

Yuping Wang

didec

Directed Dependence Coefficient

Sebastian Fuchs

Jonathan Ansari

Silhouette.coefficient function

<dl><dt>X</dt>
<dd>a data frame for a set of variables X</dd>
<dt>dend</dt>
<dd>a dendrogramm</dd>
<dt>dist.func</dt>
<dd>PD / MPD / kendall / footrule</dd>
<dt>estim.method</dt>
<dd>An optional character string specifying a method for estimating the directed dependence coefficient.</dd></dl>

Arguments

Silhouette coefficients given a dendrogram — Silhouette.coefficient

<dl>

<dt>X</dt>
<dd>a data frame for a set of variables X</dd>


<dt>dend</dt>
<dd>a dendrogramm</dd>


<dt>dist.func</dt>
<dd>PD / MPD / kendall / footrule</dd>


<dt>estim.method</dt>
<dd>An optional character string specifying a method for estimating the directed dependence coefficient.</dd>

</dl>

Silhouette.coefficient: Silhouette coefficients given a dendrogram

Description

Usage

Value

Arguments