OutlierIndex-class

.OutlierIndex

An S4 class to store the result of outlier detection.

internal

Exploration and analysis of compositional data in the
framework of Aitchison (1986, ISBN: 978-94-010-8324-9). This package
provides tools for chemical fingerprinting and source tracking of
ancient materials.

Nicolas Frerebeau

nexus

Sourcing Archaeological Materials by Chemical Composition

Anne Philippe

Brice Lebrun

Université Bordeaux Montaigne 

CNRS 

OutlierIndex-class function

<dl>
<dt><code>samples</code></dt>
<dd>A <code><a href="/link/character?package=nexus&version=0.5.0" data-mini-rdoc="nexus::character">character</a></code> vector to store the sample identifiers.</dd></dl>
<dt><code>standard</code></dt>
<dd>A <code><a href="/link/numeric?package=nexus&version=0.5.0" data-mini-rdoc="nexus::numeric">numeric</a></code> matrix giving the standard squared Mahalanobis
distances.</dd>
<dt><code>robust</code></dt>
<dd>A <code><a href="/link/numeric?package=nexus&version=0.5.0" data-mini-rdoc="nexus::numeric">numeric</a></code> matrix giving the robust squared Mahalanobis
distances.</dd>
<dt><code>limit</code></dt>
<dd>A <code><a href="/link/numeric?package=nexus&version=0.5.0" data-mini-rdoc="nexus::numeric">numeric</a></code> value giving the cut-off value used for outliers
detection (quantile of the Chi-squared distribution).</dd>
<dt><code>dof</code></dt>
<dd>A (non-negative) <code><a href="/link/numeric?package=nexus&version=0.5.0" data-mini-rdoc="nexus::numeric">numeric</a></code> value giving the degrees of freedom.</dd>

Slots

In the code snippets below, <code>x</code> is an <code>OutlierIndex</code> object.<dl>
<dt><code>as.data.frame(x)</code></dt>
<dd>Coerces to a <code><a href="/link/data.frame?package=nexus&version=0.5.0" data-mini-rdoc="nexus::data.frame">data.frame</a></code>.</dd>
</dl>

Coerce

Author

Outliers — OutlierIndex-class

<dl>
<dt><code>samples</code></dt>
<dd>A <code><a href='https://rdrr.io/r/base/character.html'>character</a></code> vector to store the sample identifiers.</dd>


<dt><code>standard</code></dt>
<dd>A <code><a href='https://rdrr.io/r/base/numeric.html'>numeric</a></code> matrix giving the standard squared Mahalanobis
distances.</dd>


<dt><code>robust</code></dt>
<dd>A <code><a href='https://rdrr.io/r/base/numeric.html'>numeric</a></code> matrix giving the robust squared Mahalanobis
distances.</dd>


<dt><code>limit</code></dt>
<dd>A <code><a href='https://rdrr.io/r/base/numeric.html'>numeric</a></code> value giving the cut-off value used for outliers
detection (quantile of the Chi-squared distribution).</dd>


<dt><code>dof</code></dt>
<dd>A (non-negative) <code><a href='https://rdrr.io/r/base/numeric.html'>numeric</a></code> value giving the degrees of freedom.</dd>


</dl>

In the code snippets below, <code>x</code> is an <code>OutlierIndex</code> object.<dl>
<dt><code>as.data.frame(x)</code></dt>
<dd>Coerces to a <code><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></code>.</dd>


</dl>

OutlierIndex-class: Outliers

Description

Arguments

Slots

Coerce

Author

See Also