Package: HRM
Version: 1.2.1
Date: 2020-02-06
Title: High-Dimensional Repeated Measures
Authors@R: c(person("Martin Happ", role = c("aut", "cre"),
                      email = "martin.happ@aon.at",
                      comment = c(ORCID = "0000-0003-0009-2665")),
	      person("Harrar W. Solomon", role = "aut"),
	      person("Arne C. Bathke", role = "aut"))
Maintainer: Martin Happ <martin.happ@aon.at>
LazyData: true
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)
Suggests: RGtk2 (>= 2.8.0), cairoDevice, testthat
LinkingTo: Rcpp
SystemRequirements: C++11
Description: 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.
License: GPL-2 | GPL-3
RoxygenNote: 7.0.2
URL: http://github.com/happma/HRM
BugReports: http://github.com/happma/HRM/issues
NeedsCompilation: yes
Packaged: 2020-02-06 14:24:38 UTC; b1011921
Author: Martin Happ [aut, cre] (<https://orcid.org/0000-0003-0009-2665>),
  Harrar W. Solomon [aut],
  Arne C. Bathke [aut]
Repository: CRAN
Date/Publication: 2020-02-06 14:50:02 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-03 14:10:25 UTC; windows
Archs: i386, x64
