optim.pca.variance.j.new

internal

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

optim.pca.variance.j.new function

<dl><dt>sym.data</dt>
<dd>An Interval Matrix</dd>
<dt>num.dimension</dt>
<dd>Number of dimensions</dd></dl>

Arguments

Optimized PCA Variance — optim.pca.variance.j.new

<dl>

<dt>sym.data</dt>
<dd>An Interval Matrix</dd>


<dt>num.dimension</dt>
<dd>Number of dimensions</dd>

</dl>

Optimized PCA Variance

optim.pca.variance.j.new: Optimized PCA Variance

Description

Usage

Value

Arguments