e_mapa

PCA plot of individuals colored by clusters

Performs an exploratory data analysis through a 'shiny' interface. It includes basic methods such as the mean, median, mode, normality test, among others. It also includes clustering techniques such as Principal Components Analysis, Hierarchical Clustering and the K-Means Method.

Oldemar Rodriguez

discoveR

Exploratory Data Analysis System

Diego Jiménez

e_mapa function

<dl><dt>pca.model</dt>
<dd>an object of class PCA [FactoMineR].</dd>
<dt>clusters</dt>
<dd>a vector specifying the cluster of each individual.</dd>
<dt>colores</dt>
<dd>a vector of color for each cluster.</dd>
<dt>ejes</dt>
<dd>a numeric vector of length 2 specifying the dimensions to be plotted.</dd>
<dt>etq</dt>
<dd>a boolean, whether to add label to graph or not.</dd></dl>

Arguments

Diego Jimenez &lt;diego.jimenez@promidat.com&gt;

Author

PCA plot of individuals colored by clusters — e_mapa

<dl>

<dt>pca.model</dt>
<dd>an object of class PCA [FactoMineR].</dd>


<dt>clusters</dt>
<dd>a vector specifying the cluster of each individual.</dd>


<dt>colores</dt>
<dd>a vector of color for each cluster.</dd>


<dt>ejes</dt>
<dd>a numeric vector of length 2 specifying the dimensions to be plotted.</dd>


<dt>etq</dt>
<dd>a boolean, whether to add label to graph or not.</dd>

</dl>

e_mapa: PCA plot of individuals colored by clusters

Description

Usage

Value

Arguments

Author

Examples