pca.nipals

Calculates principal component space using non-linear iterative partial least squares algorithm
(NIPALS)

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

pca.nipals function

<dl><dt>x</dt>
<dd>a matrix with data values (preprocessed)</dd>
<dt>ncomp</dt>
<dd>number of components to calculate</dd>
<dt>tol</dt>
<dd>tolerance (if difference in eigenvalues is smaller - convergence achieved)</dd></dl>

Arguments

NIPALS based PCA algorithm — pca.nipals

<dl>

<dt>x</dt>
<dd>a matrix with data values (preprocessed)</dd>


<dt>ncomp</dt>
<dd>number of components to calculate</dd>


<dt>tol</dt>
<dd>tolerance (if difference in eigenvalues is smaller - convergence achieved)</dd>

</dl>

pca.nipals: NIPALS based PCA algorithm

Description

Usage

Value

Arguments

References