pca_supplementary_variables

Compute loadings, correlations, contributions, and cos^2 values
for supplementary variables (columns) given component scores for the active
individuals.

High performance principal component analysis routines
that operate directly on 'bigmemory::big.matrix' objects. The
package avoids materialising large matrices in memory by
streaming data through 'BLAS' and 'LAPACK' kernels and provides
helpers to derive scores, loadings, correlations, and
contribution diagnostics, including utilities that stream
results into 'bigmemory'-backed matrices for file-based
workflows. Additional interfaces expose 'scalable' singular value
decomposition, robust PCA, and robust SVD algorithms so that
users can explore large matrices while tempering the influence
of outliers. 'Scalable' principal component analysis is also implemented,
Elgamal, Yabandeh, Aboulnaga, Mustafa, and Hefeeda (2015)
<doi:10.1145/2723372.2751520>.

Frederic Bertrand

bigPCAcpp

Principal Component Analysis for 'bigmemory' Matrices

pca_supplementary_variables function

<dl><dt>data</dt>
<dd>Matrix-like object whose columns correspond to supplementary
variables measured on the active individuals.</dd>
<dt>scores</dt>
<dd>Numeric matrix of component scores for the active individuals.</dd>
<dt>sdev</dt>
<dd>Numeric vector of component standard deviations associated with
<code>scores</code>.</dd>
<dt>center</dt>
<dd>Optional numeric vector specifying the centring to apply to each
supplementary variable. When <code>NULL</code>, column means of <code>data</code> are used.</dd></dl>

Arguments

Supplementary variable diagnostics — pca_supplementary_variables

<dl>

<dt>data</dt>
<dd>Matrix-like object whose columns correspond to supplementary
variables measured on the active individuals.</dd>


<dt>scores</dt>
<dd>Numeric matrix of component scores for the active individuals.</dd>


<dt>sdev</dt>
<dd>Numeric vector of component standard deviations associated with
<code>scores</code>.</dd>


<dt>center</dt>
<dd>Optional numeric vector specifying the centring to apply to each
supplementary variable. When <code>NULL</code>, column means of <code>data</code> are used.</dd>

</dl>

pca_supplementary_variables: Supplementary variable diagnostics

Description

Usage

Value

Arguments