HRM: High-Dimensional Repeated Measures

Methods for testing main and interaction effects in possibly high-dimensional parametric or nonparametric repeated measures in factorial designs for univariate or multivariate data. The observations of the subjects are assumed to be multivariate normal if using the parametric test. The nonparametric version tests with regard to nonparametric relative effects (based on pseudo-ranks). It is possible to use up to 2 whole- and 3 subplot factors.

Version: 1.2.1
Depends: R (≥ 3.4.0), MASS, matrixcalc, plyr, ggplot2
Imports: xtable, reshape2, tcltk, data.table, doBy, mvtnorm, Rcpp (≥ 0.12.16), pseudorank (≥ 0.3.8)
LinkingTo: Rcpp
Suggests: RGtk2 (≥ 2.8.0), cairoDevice, testthat
Published: 2020-02-06
Author: Martin Happ ORCID iD [aut, cre], Harrar W. Solomon [aut], Arne C. Bathke [aut]
Maintainer: Martin Happ <martin.happ at>
License: GPL-2 | GPL-3
NeedsCompilation: yes
SystemRequirements: C++11
Citation: HRM citation info
Materials: README
CRAN checks: HRM results


Reference manual: HRM.pdf


Package source: HRM_1.2.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): HRM_1.2.1.tgz, r-oldrel (arm64): HRM_1.2.1.tgz, r-release (x86_64): HRM_1.2.1.tgz
Old sources: HRM archive


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