unsupervised

Collection of unsupervised multiblock methods:<ul>
<li>SCA - Simultaneous Component Analysis (<code>sca</code>)</li>
<li>GCA - Generalized Canonical Analysis (<code>gca</code>)</li>
<li>GPA - Generalized Procrustes Analysis (<code>gpa</code>)</li>
<li>MFA - Multiple Factor Analysis (<code>mfa</code>)</li>
<li>PCA-GCA (<code>pcagca</code>)</li>
<li>DISCO - Distinctive and Common Components with SCA (<code>disco</code>)</li>
<li>HPCA - Hierarchical Principal component analysis (<code>hpca</code>)</li>
<li>MCOA - Multiple Co-Inertia Analysis (<code>mcoa</code>)</li>
<li>JIVE - Joint and Individual Variation Explained (<code>jive</code>)</li>
<li>STATIS - Structuration des Tableaux à Trois Indices de la Statistique (<code>statis</code>)</li>
<li>HOGSVD - Higher Order Generalized SVD (<code>hogsvd</code>)</li>
</ul>

Functions and datasets to support Smilde, Næs and Liland (2021, ISBN: 978-1-119-60096-1)
"Multiblock Data Fusion in Statistics and Machine Learning - Applications in the Natural and Life Sciences".
This implements and imports a large collection of methods for multiblock data analysis with common interfaces, result- and plotting
functions, several real data sets and six vignettes covering a range different applications.

unsupervised: Unsupervised Multiblock Methods

Description

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Details

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Examples