plot.assumptions_paruv

Plot method for objects of class <code>assumptions_paruv</code> containing
p-values produced by testing the assumptions of the parametric tests
used for comparing outputs.

A procedure for comparing multivariate samples associated with
different groups. It uses principal component analysis to convert
multivariate observations into a set of linearly uncorrelated statistical
measures, which are then compared using a number of statistical methods. The
procedure is independent of the distributional properties of samples and
automatically selects features that best explain their differences, avoiding
manual selection of specific points or summary statistics. It is appropriate
for comparing samples of time series, images, spectrometric measures or
similar multivariate observations. This package is described in Fachada et
al. (2016) <doi:10.32614/RJ-2016-055>.

Nuno Fachada

micompr

Multivariate Independent Comparison of Observations

plot.assumptions_paruv function

<dl><dt>x</dt>
<dd>Objects of class <code>assumptions_paruv</code>.</dd>
<dt>...</dt>
<dd>Extra options passed to <code><a href="/link/barplot?package=micompr&version=1.1.4" data-mini-rdoc="micompr::barplot">barplot</a></code>. The
<code>col</code> parameter defines colors for p-values below 1, 0.05 and
0.01, respectively.</dd></dl>

Arguments

Plot p-values for testing the assumptions of the parametric tests used
in output comparison — plot.assumptions_paruv

<dl>

<dt>x</dt>
<dd>Objects of class <code>assumptions_paruv</code>.</dd>


<dt>...</dt>
<dd>Extra options passed to <code><a href='https://rdrr.io/r/graphics/barplot.html'>barplot</a></code>. The
<code>col</code> parameter defines colors for p-values below 1, 0.05 and
0.01, respectively.</dd>

</dl>

plot.assumptions_paruv: Plot p-values for testing the assumptions of the parametric tests used in output comparison

Description

Usage

Value

Arguments

Details

Examples