epPCA

Principal Component Analysis (PCA) via ExPosition.

multivariate

A variety of descriptive multivariate analyses with the singular value decomposition,
such as principal components analysis, correspondence analysis, and multidimensional scaling.
See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) <doi:10.1016/j.csda.2013.11.006>.

Derek Beaton

ExPosition

Exploratory Analysis with the Singular Value Decomposition

Cherise R. Chin Fatt

Herve Abdi

epPCA function

<dl><dt>DATA</dt>
<dd>original data to perform a PCA on.</dd>
<dt>scale</dt>
<dd>a boolean, vector, or string. See <code>expo.scale</code> for
details.</dd>
<dt>center</dt>
<dd>a boolean, vector, or string. See <code>expo.scale</code> for
details.</dd>
<dt>DESIGN</dt>
<dd>a design matrix to indicate if rows belong to groups.</dd>
<dt>make_design_nominal</dt>
<dd>a boolean. If TRUE (default), DESIGN is a vector
that indicates groups (and will be dummy-coded). If FALSE, DESIGN is a
dummy-coded matrix.</dd>
<dt>graphs</dt>
<dd>a boolean. If TRUE (default), graphs and plots are provided
(via <code>epGraphs</code>)</dd>
<dt>k</dt>
<dd>number of components to return.</dd></dl>

Arguments

Author

epPCA: Principal Component Analysis (PCA) via ExPosition. — epPCA

<dl>

<dt>DATA</dt>
<dd>original data to perform a PCA on.</dd>


<dt>scale</dt>
<dd>a boolean, vector, or string. See <code>expo.scale</code> for
details.</dd>


<dt>center</dt>
<dd>a boolean, vector, or string. See <code>expo.scale</code> for
details.</dd>


<dt>DESIGN</dt>
<dd>a design matrix to indicate if rows belong to groups.</dd>


<dt>make_design_nominal</dt>
<dd>a boolean. If TRUE (default), DESIGN is a vector
that indicates groups (and will be dummy-coded). If FALSE, DESIGN is a
dummy-coded matrix.</dd>


<dt>graphs</dt>
<dd>a boolean. If TRUE (default), graphs and plots are provided
(via <code>epGraphs</code>)</dd>


<dt>k</dt>
<dd>number of components to return.</dd>

</dl>

epPCA: epPCA: Principal Component Analysis (PCA) via ExPosition.

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples