pca.supplementary.vertex.fun.j.new

Symbolic Data Analysis (SDA) was proposed by professor Edwin Diday in 1987, the main purpose of SDA is to substitute the set of rows (cases) in the data table for  a concept (second order statistical unit). This package implements, to the symbolic case, certain techniques of automatic classification, as well as some linear models.

Oldemar Rodriguez

RSDA

R to Symbolic Data Analysis

Jose Emmanuel Chacon

Carlos Aguero

Jorge Arce

pca.supplementary.vertex.fun.j.new function

<dl><dt>x</dt>
<dd>A Matrix</dd>
<dt>N</dt>
<dd>Number of concepts</dd>
<dt>M</dt>
<dd>Number of variables</dd>
<dt>sym.var.names</dt>
<dd>Names of concepts</dd>
<dt>sym.data.vertex.matrix</dt>
<dd>Vertex Matrix</dd>
<dt>tot.individuals</dt>
<dd>Number of individuals</dd></dl>

Arguments

Calculate the distance — pca.supplementary.vertex.fun.j.new

<dl>

<dt>x</dt>
<dd>A Matrix</dd>


<dt>N</dt>
<dd>Number of concepts</dd>


<dt>M</dt>
<dd>Number of variables</dd>


<dt>sym.var.names</dt>
<dd>Names of concepts</dd>


<dt>sym.data.vertex.matrix</dt>
<dd>Vertex Matrix</dd>


<dt>tot.individuals</dt>
<dd>Number of individuals</dd>

</dl>

pca.supplementary.vertex.fun.j.new: Calculate the distance

Description

Usage

Value

Arguments