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RRPP
View on CRAN: Click
here
Download and install RRPP package within the R console
Install from CRAN:
install.packages("RRPP")
Install from Github:
library("remotes")
install_github("cran/RRPP")
Install by package version:
library("remotes")
install_version("RRPP", "2.1.2")
Attach the package and use:
library("RRPP")
Maintained by
Michael Collyer
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.RRPP . https://github.com/mlcollyer/RRPP . RRPP citation info . RRPP results . RRPP.pdf . ANOVA versus MANOVA in RRPP . Using RRPP . RRPP_2.1.2.tar.gz . RRPP_2.1.2.zip . RRPP_2.1.2.zip . RRPP_2.1.2.zip . RRPP_2.1.2.tgz . RRPP_2.1.2.tgz . RRPP_2.1.2.tgz . RRPP_2.1.2.tgz . RRPP archive . https://CRAN.R-project.org/package=RRPP .
First Published: 2018-01-22
Latest Update: 2024-02-06
Description:
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.
How to cite:
Michael Collyer (2018). RRPP: Linear Model Evaluation with Randomized Residuals in a Permutation Procedure. R package version 2.1.2, https://cran.r-project.org/web/packages/RRPP. Accessed 16 Apr. 2025.
Previous versions and publish date:
0.1.0 (2018-01-22 15:40), 0.2.0 (2018-04-22 19:40), 0.3.0 (2018-07-23 23:10), 0.4.0 (2019-03-24 19:36), 0.4.1 (2019-04-02 19:22), 0.4.2 (2019-05-19 23:40), 0.4.3 (2019-10-07 22:50), 0.5.0 (2019-12-19 14:40), 0.5.1 (2020-01-19 21:00), 0.5.2 (2020-01-26 19:40), 0.6.0 (2020-05-28 18:40), 0.6.1 (2020-06-24 18:10), 0.6.2 (2021-01-11 16:10), 1.0.0 (2021-03-30 08:50), 1.1.0 (2021-10-09 17:40), 1.1.1 (2021-10-24 17:20), 1.1.2 (2021-11-04 14:40), 1.2.1 (2022-03-01 18:30), 1.2.2 (2022-03-10 13:20), 1.2.3 (2022-03-19 15:50), 1.3.0 (2022-06-21 18:00), 1.3.1 (2022-09-12 20:10), 1.4.0 (2023-08-15 21:00), 2.0.0 (2024-02-06 15:30), 2.0.1 (2024-06-04 23:30), 2.0.2 (2024-06-12 17:50), 2.0.3 (2024-06-22 18:40), 2.0.4 (2024-11-14 05:50), 2.1.0 (2025-02-01 01:30), 2.1.1 (2025-02-09 23:40)
Other packages that cited RRPP R package
View RRPP citation profile
Other R packages that RRPP depends,
imports, suggests or enhances
Complete documentation for RRPP
Functions, R codes and Examples using
the RRPP R package
Some associated functions: PlethMorph . Pupfish . PupfishHeads . RRPP-package . add.trajectories . add.tree . anova.lm.rrpp . classify . coef.lm.rrpp . convert2ggplot . fitted.lm.rrpp . lm.rrpp . logLik.lm.rrpp . looCV . manova.update . model.comparison . model.frame.lm.rrpp . model.matrix.lm.rrpp . motionpaths . na.omit.rrpp.data.frame . ordinate . pairwise . plot.lm.rrpp . plot.looCV . plot.model.comparison . plot.ordinate . plot.predict.lm.rrpp . plot.trajectory.analysis . predict.lm.rrpp . prep.lda . print.anova.lm.rrpp . print.coef.lm.rrpp . print.lm.rrpp . print.looCV . print.model.comparison . print.ordinate . print.pairwise . print.predict.lm.rrpp . print.summary.lm.rrpp . print.summary.manova.lm.rrpp . print.summary.ordinate . print.summary.pairwise . print.summary.trajectory.analysis . print.trajectory.analysis . residuals.lm.rrpp . reveal.model.designs . rrpp.data.frame . scaleCov . summary.anova.lm.rrpp . summary.coef.lm.rrpp . summary.lm.rrpp . summary.looCV . summary.manova.lm.rrpp . summary.model.comparison . summary.ordinate . summary.pairwise . summary.predict.lm.rrpp . summary.trajectory.analysis . terms.lm.rrpp . trajectory.analysis . vec.cor.matrix .
Some associated R codes: deprecated.defunct.R . Full RRPP package functions and examples
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