plot.PCA.Analysis

Plots the results of a Principal Component Analysis.

Several multivariate techniques from a biplot perspective. It is the translation (with many improvements) into R of the previous package developed in 'Matlab'. The package contains some of the main developments of my team during the last 30 years together with some more standard techniques. Package includes: Classical Biplots, HJ-Biplot, Canonical Biplots, MANOVA Biplots, Correspondence Analysis, Canonical Correspondence Analysis, Canonical STATIS-ACT, Logistic Biplots for binary and ordinal data, Multidimensional Unfolding, External Biplots for Principal Coordinates Analysis or Multidimensional Scaling, among many others. References can be found in the help of each procedure.

Jose Vicente-Villardon

MultBiplotR

Multivariate Analysis Using Biplots in R

plot.PCA.Analysis function

<dl> <dt>x</dt>
<dd>The object with the results of a PCA</dd> <dt>A1</dt>
<dd>Dimension for the first axis of the representation</dd> <dt>A2</dt>
<dd>Dimension for the second axis of the representation</dd> <dt>CorrelationCircle</dt>
<dd>Should the correlation circle be plotted? If false the scores plot is done.</dd> <dt>...</dt>
<dd>Any other arguments of the function plot.ContinuousBiplot</dd></dl>

Arguments

Author

Plots a Principal Component Analysis — plot.PCA.Analysis

<dl>

 <dt>x</dt>
<dd>The object with the results of a PCA</dd>

 <dt>A1</dt>
<dd>Dimension for the first axis of the representation</dd>

 <dt>A2</dt>
<dd>Dimension for the second axis of the representation</dd>

 <dt>CorrelationCircle</dt>
<dd>Should the correlation circle be plotted? If false the scores plot is done.</dd>

 <dt>...</dt>
<dd>Any other arguments of the function plot.ContinuousBiplot</dd>

</dl>

plot.PCA.Analysis: Plots a Principal Component Analysis

Description

Usage

Value

Arguments

Author

Details

See Also

Examples