pca.svd

Computes principal component space using Singular Values Decomposition

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.svd function

<dl><dt>x</dt>
<dd>a matrix with data values (preprocessed)</dd>
<dt>ncomp</dt>
<dd>number of components to calculate</dd></dl>

Arguments

Singular Values Decomposition based PCA algorithm — pca.svd

<dl>

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


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

</dl>

pca.svd: Singular Values Decomposition based PCA algorithm

Description

Usage

Value

Arguments