corcomp

covcomp

cov2cor

<code>covcomp</code> returns the variance-covariance matrix of the
 components P on S, and <code>corcomp</code> returns the correlation matrix.

multivariate

Simple Component Analysis (SCA) often provides much more
interpretable components than Principal Components (PCA) while still
representing much of the variability in the data.

Martin Maechler

Simple Component Analysis

corcomp function

<dl> <dt>S</dt>
<dd>correlation/covariance matrix of the \(p\) original variables.</dd> <dt>P</dt>
<dd>component matrix of dimension \(p \times b\).</dd> <dt>V</dt>
<dd>symmetric numeric matrix, usually positive definite such as a
 covariance matrix.</dd></dl>

Arguments

Valentin Rousson <a href="/link/rousson%40ifspm.unizh.ch?package=sca&version=0.9-2" data-mini-rdoc="sca::rousson@ifspm.unizh.ch">rousson@ifspm.unizh.ch</a> and
 Martin Maechler <a href="/link/maechler%40stat.math.ethz.ch?package=sca&version=0.9-2" data-mini-rdoc="sca::maechler@stat.math.ethz.ch">maechler@stat.math.ethz.ch</a>.

Author

Covariance and Correlation Matrix of Components P on S — corcomp

<dl>

 <dt>S</dt>
<dd>correlation/covariance matrix of the \(p\) original variables.</dd>

 <dt>P</dt>
<dd>component matrix of dimension \(p \times b\).</dd>

 <dt>V</dt>
<dd>symmetric numeric matrix, usually positive definite such as a
 covariance matrix.</dd>

</dl>

Valentin Rousson <a href='mailto:rousson@ifspm.unizh.ch'>rousson@ifspm.unizh.ch</a> and
 Martin Maechler <a href='mailto:maechler@stat.math.ethz.ch'>maechler@stat.math.ethz.ch</a>.

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corcomp: Covariance and Correlation Matrix of Components P on S

Description

Usage

Value

Arguments

Author

See Also

Examples