categorize.pca

The method compares score and orthogonal distances of PCA results from <code>res</code> with
critical limits computed for the PCA model and categorizes the corresponding objects as
"regular", "extreme" or "outlier".

Projection based methods for preprocessing, exploring and analysis of multivariate data used in chemometrics. S. Kucheryavskiy (2020) <doi:10.1016/j.chemolab.2020.103937>.

Sergey Kucheryavskiy

mdatools

Multivariate Data Analysis for Chemometrics

categorize.pca function

<dl><dt>obj</dt>
<dd>object with PCA model</dd>
<dt>res</dt>
<dd>object with PCA results</dd>
<dt>ncomp</dt>
<dd>number of components to use for the categorization</dd>
<dt>...</dt>
<dd>other parameters</dd></dl>

Arguments

Categorize PCA results based on orthogonal and score distances. — categorize.pca

<dl>

<dt>obj</dt>
<dd>object with PCA model</dd>


<dt>res</dt>
<dd>object with PCA results</dd>


<dt>ncomp</dt>
<dd>number of components to use for the categorization</dd>


<dt>...</dt>
<dd>other parameters</dd>

</dl>

categorize.pca: Categorize PCA results based on orthogonal and score distances.

Description

Usage

Value

Arguments

Details