colCardinalities

Computes the cardinality (the number of non-zero elements) of each column of
the matrix \(\mathbf{w}\).

Two implementations of canonical correlation analysis
(CCA) that are based on iterated regression. By choosing the
appropriate regression algorithm for each data domain, it is
possible to enforce sparsity, non-negativity or other kinds of
constraints on the projection vectors. Multiple canonical
variables are computed sequentially using a generalized
deflation scheme, where the additional correlation not
explained by previous variables is maximized. nscancor() is
used to analyze paired data from two domains, and has the same
interface as cancor() from the 'stats' package (plus some extra
parameters). mcancor() is appropriate for analyzing data from
three or more domains. See
<https://sigg-iten.ch/learningbits/2014/01/20/canonical-correlation-analysis-under-constraints/>
and Sigg et al. (2007) <doi:10.1109/MLSP.2007.4414315> for more
details.

Christian Sigg

nscancor

Non-Negative and Sparse CCA

R Core
team 

colCardinalities function

<dl><dt>w</dt>
<dd>a numeric matrix, e.g. <code>xcoef</code> as returned by <code>nscancor</code></dd></dl>

Arguments

Cardinality of Column Vectors — colCardinalities

<dl>

<dt>w</dt>
<dd>a numeric matrix, e.g. <code>xcoef</code> as returned by <code>nscancor</code></dd>

</dl>

colCardinalities: Cardinality of Column Vectors

Description

Usage

Value

Arguments

Examples