RRPP: Linear Model Evaluation with Randomized Residuals in a Permutation Procedure

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) <doi:10.1111/2041-210X.13029>. 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: 0.6.1
Depends: R (≥ 3.5.0)
Imports: parallel, ape
Suggests: knitr, rmarkdown, testthat
Published: 2020-06-24
Author: Michael Collyer [aut, cre], Dean Adams [aut]
Maintainer: Michael Collyer <mlcollyer at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/mlcollyer/RRPP
NeedsCompilation: no
Citation: RRPP citation info
Materials: README NEWS
CRAN checks: RRPP results


Reference manual: RRPP.pdf
Vignettes: ANOVA versus MANOVA in RRPP
Using RRPP
Package source: RRPP_0.6.1.tar.gz
Windows binaries: r-devel: RRPP_0.6.1.zip, r-release: RRPP_0.6.1.zip, r-oldrel: RRPP_0.6.1.zip
macOS binaries: r-release: RRPP_0.6.1.tgz, r-oldrel: RRPP_0.6.1.tgz
Old sources: RRPP archive

Reverse dependencies:

Reverse depends: geomorph
Reverse suggests: vcvComp


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