MultivariateSummary

.MultivariateSummary

MultivariateSummary-class

SummaryCA-class

.SummaryCA

SummaryPCA-class

.SummaryPCA

A virtual S4 class to store the summary of a multivariate data analysis.

internal

Simple Principal Components Analysis (PCA) and (Multiple)
Correspondence Analysis (CA) based on the Singular Value Decomposition
(SVD). This package provides S4 classes and methods to compute,
extract, summarize and visualize results of multivariate data
analysis. It also includes methods for partial bootstrap validation
described in Greenacre (1984, ISBN: 978-0-12-299050-2) and Lebart et
al. (2006, ISBN: 978-2-10-049616-7).

Nicolas Frerebeau

dimensio

Multivariate Data Analysis

Jean-Baptiste Fourvel

Brice Lebrun

Université Bordeaux Montaigne 

CNRS 

MultivariateSummary function

<dl>
<dt><code>data</code></dt>
<dd>A <code><a href="/link/numeric?package=dimensio&version=0.10.1" data-mini-rdoc="dimensio::numeric">numeric</a></code> <code><a href="/link/matrix?package=dimensio&version=0.10.1" data-mini-rdoc="dimensio::matrix">matrix</a></code>.</dd></dl>
<dt><code>eigenvalues</code></dt>
<dd>A <code><a href="/link/numeric?package=dimensio&version=0.10.1" data-mini-rdoc="dimensio::numeric">numeric</a></code> <code><a href="/link/matrix?package=dimensio&version=0.10.1" data-mini-rdoc="dimensio::matrix">matrix</a></code>.</dd>
<dt><code>results</code></dt>
<dd>A <code><a href="/link/numeric?package=dimensio&version=0.10.1" data-mini-rdoc="dimensio::numeric">numeric</a></code> <code><a href="/link/matrix?package=dimensio&version=0.10.1" data-mini-rdoc="dimensio::matrix">matrix</a></code>.</dd>
<dt><code>supplement</code></dt>
<dd>A <code><a href="/link/logical?package=dimensio&version=0.10.1" data-mini-rdoc="dimensio::logical">logical</a></code> vector specifying the supplementary points.</dd>
<dt><code>margin</code></dt>
<dd>An <code><a href="/link/integer?package=dimensio&version=0.10.1" data-mini-rdoc="dimensio::integer">integer</a></code>.</dd>

Slots

Author

Summary of Multivariate Data Analysis — MultivariateSummary

<dl>
<dt><code>data</code></dt>
<dd>A <code><a href='https://rdrr.io/r/base/numeric.html'>numeric</a></code> <code><a href='https://rdrr.io/r/base/matrix.html'>matrix</a></code>.</dd>


<dt><code>eigenvalues</code></dt>
<dd>A <code><a href='https://rdrr.io/r/base/numeric.html'>numeric</a></code> <code><a href='https://rdrr.io/r/base/matrix.html'>matrix</a></code>.</dd>


<dt><code>results</code></dt>
<dd>A <code><a href='https://rdrr.io/r/base/numeric.html'>numeric</a></code> <code><a href='https://rdrr.io/r/base/matrix.html'>matrix</a></code>.</dd>


<dt><code>supplement</code></dt>
<dd>A <code><a href='https://rdrr.io/r/base/logical.html'>logical</a></code> vector specifying the supplementary points.</dd>


<dt><code>margin</code></dt>
<dd>An <code><a href='https://rdrr.io/r/base/integer.html'>integer</a></code>.</dd>


</dl>

Summary of Multivariate Data Analysis

MultivariateSummary: Summary of Multivariate Data Analysis

Description

Arguments

Slots

Author

See Also