varianceOnEvecs

Project the sample points stored in the rows of <code>X</code> along the
eigenvectors of <code>Q</code> and find the variance along each of the
projections.

Implements adaptive gPCA, as described in: Fukuyama, J. (2017)
<arXiv:1702.00501>. The package also includes functionality for applying
the method to 'phyloseq' objects so that the method can be easily applied
to microbiome data and a 'shiny' app for interactive visualization.

Julia Fukuyama

adaptiveGPCA

Adaptive Generalized PCA

varianceOnEvecs function

<dl><dt>X</dt>
<dd>An \(n \times p\) data matrix, each row corresponding to a sample.</dd>
<dt>Q</dt>
<dd>A \(p \times p\) similarity matrix, either as a matrix
or as its eigendecomposition (the output from <code>eigen</code>).</dd></dl>

Arguments

Variance along eigenvectors of Q — varianceOnEvecs

<dl>

<dt>X</dt>
<dd>An \(n \times p\) data matrix, each row corresponding to a sample.</dd>


<dt>Q</dt>
<dd>A \(p \times p\) similarity matrix, either as a matrix
or as its eigendecomposition (the output from <code>eigen</code>).</dd>

</dl>

varianceOnEvecs: Variance along eigenvectors of Q

Description

Usage

Value

Arguments

Examples