plot.interSubVar

This function produces a heat map for inter-subject variability, based on 
results from a <code>measurement.error</code> object. The function, 
<code>interSubVar</code>, must first be used on the <code>measurement.error</code> 
object to obtain variability statistics. This function use the <code><a href="/link/image?package=RRPP&version=2.0.3" data-mini-rdoc="RRPP::image">image</a></code>
function to produce plots. It does little to manipulate such plots, but any
argument for <code><a href="/link/image?package=RRPP&version=2.0.3" data-mini-rdoc="RRPP::image">image</a></code> can be manipulated here, as well as the graphical
parameters that can be adjusted within <code><a href="/link/image?package=RRPP&version=2.0.3" data-mini-rdoc="RRPP::image">image</a></code>.

utilities

Linear model calculations are made for many random versions of data.
Using residual randomization in a permutation procedure, sums of squares are
calculated over many permutations to generate empirical probability distributions
for evaluating model effects.  This packaged is described by
Collyer & Adams (2018).  Additionally, coefficients, statistics, fitted values, and residuals generated over many
permutations can be used for various procedures including pairwise tests, prediction, classification, and
model comparison.  This package should provide most tools one could need for the analysis of
high-dimensional data, especially in ecology and evolutionary biology, but certainly other fields, as well.

Michael Collyer

RRPP

Linear Model Evaluation with Randomized Residuals in a
Permutation Procedure

Dean Adams

plot.interSubVar function

<dl><dt>x</dt>
<dd>Object from <code>interSubVar</code></dd>
<dt>...</dt>
<dd>Arguments passed onto <code><a href="/link/image?package=RRPP&version=2.0.3" data-mini-rdoc="RRPP::image">image</a></code> and <code><a href="/link/plot?package=RRPP&version=2.0.3" data-mini-rdoc="RRPP::plot">plot</a></code>.</dd></dl>

Arguments

Author

This function produces a heat map for inter-subject variability, based on 
results from a <code>measurement.error</code> object. The function, 
<code>interSubVar</code>, must first be used on the <code>measurement.error</code> 
object to obtain variability statistics. This function use the <code><a href='https://rdrr.io/r/graphics/image.html'>image</a></code>
function to produce plots. It does little to manipulate such plots, but any
argument for <code><a href='https://rdrr.io/r/graphics/image.html'>image</a></code> can be manipulated here, as well as the graphical
parameters that can be adjusted within <code><a href='https://rdrr.io/r/graphics/image.html'>image</a></code>.

Plot Function for RRPP — plot.interSubVar

<dl>

<dt>x</dt>
<dd>Object from <code>interSubVar</code></dd>


<dt>...</dt>
<dd>Arguments passed onto <code><a href='https://rdrr.io/r/graphics/image.html'>image</a></code> and <code><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></code>.</dd>

</dl>

plot.interSubVar: Plot Function for RRPP

Description

Usage

Arguments

Author