pow_o2m2

internal

Performs the O2PLS data integration method for two datasets, yielding joint and data-specific parts for each dataset.
The algorithm automatically switches to a memory-efficient approach to fit O2PLS to high dimensional data.
It provides a rigorous and a faster alternative cross-validation method to select the number of components,
as well as functions to report proportions of explained variation and to construct plots of the results.
See the software article by el Bouhaddani et al (2018) <doi:10.1186/s12859-018-2371-3>,
and Trygg and Wold (2003) <doi:10.1002/cem.775>.
It also performs Sparse Group (Penalized) O2PLS, see Gu et al (2020) <doi:10.1186/s12859-021-03958-3> and cross-validation for the degree of sparsity.

Said Bouhaddani

OmicsPLS

Data Integration with Two-Way Orthogonal Partial Least Squares

Said el Bouhaddani

Zander Gu

Jeanine Houwing-Duistermaat

Geurt Jongbloed

Szymon Kielbasa

Hae-Won Uh

pow_o2m2 function

<dl><dt>X</dt>
<dd>Numeric matrix. Vectors will be coerced to matrix with <code>as.matrix</code> (if this is possible)</dd>
<dt>Y</dt>
<dd>Numeric matrix. Vectors will be coerced to matrix with <code>as.matrix</code> (if this is possible)</dd>
<dt>n</dt>
<dd>Integer. Number of joint PLS components. Must be positive.</dd>
<dt>tol</dt>
<dd>Double. Threshold for which the NIPALS method is deemed converged. Must be positive.</dd>
<dt>max_iterations</dt>
<dd>Integer. Maximum number of iterations for the NIPALS method.</dd></dl>

Arguments

Power method for PLS2 — pow_o2m2

<dl>

<dt>X</dt>
<dd>Numeric matrix. Vectors will be coerced to matrix with <code>as.matrix</code> (if this is possible)</dd>


<dt>Y</dt>
<dd>Numeric matrix. Vectors will be coerced to matrix with <code>as.matrix</code> (if this is possible)</dd>


<dt>n</dt>
<dd>Integer. Number of joint PLS components. Must be positive.</dd>


<dt>tol</dt>
<dd>Double. Threshold for which the NIPALS method is deemed converged. Must be positive.</dd>


<dt>max_iterations</dt>
<dd>Integer. Maximum number of iterations for the NIPALS method.</dd>

</dl>

Power method for PLS2

pow_o2m2: Power method for PLS2

Description

Usage

Arguments

Details

See Also