Package: rrscale
Title: Robust Re-Scaling to Better Recover Latent Effects in Data
Version: 1.0
Authors@R: c(person("Gregory", "Hunt", email = "ghunt@wm.edu", role = c("aut", "cre")),person("Johann", "Gagnon-Bartsch", email = "johanngb@umich.edu", role = c("aut")))
Description: Non-linear transformations of data to better discover latent effects. Applies a sequence of three transformations (1) a Gaussianizing transformation, (2) a Z-score transformation, and (3) an outlier removal transformation. A publication describing the method has the following citation: Gregory J. Hunt, Mark A. Dane, James E. Korkola, Laura M. Heiser & Johann A. Gagnon-Bartsch (2020) "Automatic Transformation and Integration to Improve Visualization and Discovery of Latent Effects in Imaging Data", Journal of Computational and Graphical Statistics, <doi:10.1080/10618600.2020.1741379>.
Date: 2020-5-22
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Imports: DEoptim, nloptr, abind
Suggests: knitr, rmarkdown, testthat, ggplot2, reshape2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-05-25 23:56:10 UTC; greg
Author: Gregory Hunt [aut, cre],
  Johann Gagnon-Bartsch [aut]
Maintainer: Gregory Hunt <ghunt@wm.edu>
Repository: CRAN
Date/Publication: 2020-05-26 11:30:02 UTC
Built: R 4.6.0; ; 2026-04-25 22:02:27 UTC; unix
