pval

A function to find the probability of values greater or lesser than target,
from a vector of values presumably obtained in random permutations.

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

pval function

<dl><dt>s</dt>
<dd>The sampling distribution vector to use.</dd>
<dt>target</dt>
<dd>The value to target in the distribution. (If null, the first value
in the vector is used.). If the target exists outside the range of s,
a probability of 0 or 1 is certain.</dd>
<dt>greater</dt>
<dd>Logical value for whether the probability should be "greater than 
or equal to". Change to greater = FALSE for "less than or equal to".</dd></dl>

Arguments

Author

Obtain P-value from a vector of values — pval

<dl>

<dt>s</dt>
<dd>The sampling distribution vector to use.</dd>


<dt>target</dt>
<dd>The value to target in the distribution. (If null, the first value
in the vector is used.). If the target exists outside the range of s,
a probability of 0 or 1 is certain.</dd>


<dt>greater</dt>
<dd>Logical value for whether the probability should be "greater than 
or equal to". Change to greater = FALSE for "less than or equal to".</dd>

</dl>

pval: Obtain P-value from a vector of values

Description

Usage

Arguments

Author