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 method is described by Collyer, Sekora, & Adams (2015) . 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.


RRPP is a software package for evaluating linear models with residual randomization in a permutation procedure. S3 Generic used for the lm function can also be used with lm.rrpp, with the chief difference being that lm coefficients, fitted values, and residuals are estimated many times with random permutations of data.

To install the current RRPP R-package from CRAN:

Within R:

install.packages("RRPP")

To install the current version of geomorph R-package from Github using devtools:

Within R:

install.packages("devtools")

devtools::install_github("mlcollyer/RRPP")

The version on github is updated regularly, especially if errors or programming bugs are discovered.

News

CHANGES IN RRPP VERSION 0.3.0

NEW FEATURES o Added model.comparison function. o Added classify function. OTHER CHANGES o Added a pairwise variance comparison for the pairwise function. BUG FIXES o Fixed some issues with univariate data for classify. o Fixed some issues with univariate data for pairwise. o Fixed the logL function within model.comparisons for GLS determinants (was returning 0). o Fixed some issues with the aov.multimodel subfunction of anova.lm.rrpp, related to GLS permutations and intercept only models.
o Added random SS output to aov.multimodel subfunction of anova.lm.rrpp, so that it can be called by other functions/packages.

CHANGES IN RRPP VERSION 0.2.0

NEW FEATURES o pairwise function: allows pairwise comparison of means or slopes for a lm.rrpp fit. o A vignette for using RRPP, which is the same as Appendix S2 in Collyer and Adams (2008). RRPP: An R package for fitting linear models to high-dimensional data using residual randomization. Methods in Ecology and Evolution. (submitted)

OTHER CHANGES o Added multi-model inference capabaility to anova.lm.rrpp

BUG FIXES o Fixed issue for coef.lm.rrpp tests when type II or type III SS is chosen, to make sure that appropriate coefficients are used.

CHANGES IN RRPP VERSION 0.1.0

New Release!

New features
	anova.lm.rrpp.r
	coef.lm.rrpp.r
	lm.rrpp.r
	predict.lm.rrpp.r
	RRPP.support.code.r
	RRPP.utils.r

Reference manual

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install.packages("RRPP")

0.3.0 by Michael Collyer, 7 months ago


https://github.com/mlcollyer/RRPP


Browse source code at https://github.com/cran/RRPP


Authors: Michael Collyer , Dean Adams


Documentation:   PDF Manual  


GPL (>= 2) license


Suggests knitr, rmarkdown, testthat


Imported by geomorph.


See at CRAN