rrscale - Robust Re-Scaling to Better Recover Latent Effects in Data
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>.
