RRPP: Linear Model Evaluation with Randomized Residuals in a Permutation Procedure (original) (raw)

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.

Version: 2.0.3
Depends: R (≥ 4.4.0)
Imports: parallel, ape, ggplot2, Matrix
Suggests: knitr, rmarkdown, testthat (≥ 3.2.0), dplyr, tibble
Published: 2024-06-22
DOI: 10.32614/CRAN.package.RRPP
Author: Michael Collyer ORCID iD [aut, cre], Dean Adams ORCID iD [aut]
Maintainer: Michael Collyer
License: GPL (≥ 3)
URL: https://github.com/mlcollyer/RRPP
NeedsCompilation: no
Citation: RRPP citation info
Materials: README NEWS
In views: Phylogenetics
CRAN checks: RRPP results

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