pcaVarexpl

Diagnostics of PCA to see the explained variance for each variable.

 multivariate

R companion to the book "Introduction to Multivariate Statistical Analysis in Chemometrics" written by K. Varmuza and P. Filzmoser (2009).

Peter Filzmoser

chemometrics

Multivariate Statistical Analysis in Chemometrics

pcaVarexpl function

<dl> <dt>X</dt>
<dd>numeric data frame or matrix</dd> <dt>a</dt>
<dd>number of principal components</dd> <dt>center</dt>
<dd>centring of X (FALSE or TRUE)</dd> <dt>scale</dt>
<dd>scaling of X (FALSE or TRUE)</dd> <dt>plot</dt>
<dd>if TRUE make plot with explained variance</dd> <dt>...</dt>
<dd>additional graphics parameters, see <code><a href="/link/par?package=chemometrics&version=1.4.4" data-mini-rdoc="chemometrics::par">par</a></code></dd></dl>

Arguments

Peter Filzmoser &lt;P.Filzmoser@tuwien.ac.at&gt;

Author

PCA diagnostics for variables — pcaVarexpl

<dl>

 <dt>X</dt>
<dd>numeric data frame or matrix</dd>

 <dt>a</dt>
<dd>number of principal components</dd>

 <dt>center</dt>
<dd>centring of X (FALSE or TRUE)</dd>

 <dt>scale</dt>
<dd>scaling of X (FALSE or TRUE)</dd>

 <dt>plot</dt>
<dd>if TRUE make plot with explained variance</dd>

 <dt>...</dt>
<dd>additional graphics parameters, see <code><a href='https://rdrr.io/r/graphics/par.html'>par</a></code></dd>

</dl>

pcaVarexpl: PCA diagnostics for variables

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples