plot.mvn

Generates diagnostic plots for objects of class <code>mvn</code>, including multivariate Q-Q plots,
3D or contour kernel density plots, univariate plots (e.g., Q-Q, histograms, boxplots),
and multivariate outlier detection plots. If a grouping variable (subset) was used in the
<code>mvn</code> function, plots will be generated separately for each group.

A comprehensive suite for assessing multivariate normality using six statistical tests
(Mardia, Henze–Zirkler, Henze–Wagner, Royston, Doornik–Hansen, Energy).
Also includes univariate diagnostics, bivariate density visualization, robust outlier
detection, power transformations (e.g., Box–Cox, Yeo–Johnson), and imputation strategies
("mean", "median", "mice") for handling missing data. Bootstrap resampling is supported
for selected tests to improve p-value accuracy in small samples.
Diagnostic plots are available via both 'ggplot2' and interactive 'plotly' visualizations. See Korkmaz et al. (2014) <https://journal.r-project.org/archive/2014-2/korkmaz-goksuluk-zararsiz.pdf>.

Selcuk Korkmaz

Multivariate Normality Tests

Dincer Goksuluk

Gokmen Zararsiz

plot.mvn function

<dl><dt>x</dt>
<dd>An object of class <code>mvn</code>, as returned by the <code>mvn</code> function.</dd>
<dt>...</dt>
<dd>Additional arguments passed to internal plotting functions:
<code>diagnostic</code> (<code>"multivariate"</code>, <code>"univariate"</code>, <code>"outlier"</code>),
<code>type</code> (e.g., <code>"qq"</code>, <code>"boxplot"</code>, <code>"persp"</code>),
<code>interactive</code> (logical; use plotly), and</dd></dl>

Arguments

Plot Diagnostics for Multivariate Normality Analysis — plot.mvn

<dl>

<dt>x</dt>
<dd>An object of class <code>mvn</code>, as returned by the <code>mvn</code> function.</dd>


<dt>...</dt>
<dd>Additional arguments passed to internal plotting functions:
<code>diagnostic</code> (<code>"multivariate"</code>, <code>"univariate"</code>, <code>"outlier"</code>),
<code>type</code> (e.g., <code>"qq"</code>, <code>"boxplot"</code>, <code>"persp"</code>),
<code>interactive</code> (logical; use plotly), and</dd>

</dl>

plot.mvn: Plot Diagnostics for Multivariate Normality Analysis

Description

Usage

Value

Arguments

Examples