getResCov

A function mostly for internal processing but can be used to extract the residual
covariance matrix. This matrix is the residual covariance matrix,
not the model covariance matrix used for estimation (see <code>getModelCov</code>). 
Options for averaging over degrees of freedom or number of
observations, plus standardization, are also available.

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

getResCov function

<dl><dt>fit</dt>
<dd>Object from <code>lm.rrpp</code></dd>
<dt>useDf</dt>
<dd>Logical value for whether the degrees of freedom from the linear model
fit should be used (if TRUE), as opposed to the number of observations (if FALSE).</dd>
<dt>standardize</dt>
<dd>Logical value for whether residuals should be standardized. If TRUE,
a correlation matrix is produced.</dd></dl>

Arguments

Author

Utility Function for RRPP — getResCov

<dl>

<dt>fit</dt>
<dd>Object from <code>lm.rrpp</code></dd>


<dt>useDf</dt>
<dd>Logical value for whether the degrees of freedom from the linear model
fit should be used (if TRUE), as opposed to the number of observations (if FALSE).</dd>


<dt>standardize</dt>
<dd>Logical value for whether residuals should be standardized. If TRUE,
a correlation matrix is produced.</dd>

</dl>

getResCov: Utility Function for RRPP

Description

Usage

Arguments

Author