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 |
Maintainer: | Martin Happ <martin.happ at aon.at> |
BugReports: | http://github.com/happma/HRM/issues |
License: | GPL-2 | GPL-3 |
URL: | http://github.com/happma/HRM |
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: HRM_1.2.1.zip, r-release: HRM_1.2.1.zip, r-oldrel: HRM_1.2.1.zip |
macOS binaries: | r-release: HRM_1.2.1.tgz, r-oldrel: HRM_1.2.1.tgz |
Old sources: | HRM archive |
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