bestNormalize: Normalizing Transformation Functions

Estimate a suite of normalizing transformations, including a new adaptation of a technique based on ranks which can guarantee normally distributed transformed data if there are no ties: ordered quantile normalization (ORQ). ORQ normalization combines a rank-mapping approach with a shifted logit approximation that allows the transformation to work on data outside the original domain. It is also able to handle new data within the original domain via linear interpolation. The package is built to estimate the best normalizing transformation for a vector consistently and accurately. It implements the Box-Cox transformation, the Yeo-Johnson transformation, three types of Lambert WxF transformations, and the ordered quantile normalization transformation.

Version: 1.2.0
Depends: R (≥ 3.1.0)
Imports: LambertW, nortest
Suggests: knitr, rmarkdown, MASS, testthat, mgcv, parallel
Published: 2018-05-30
Author: Ryan Andrew Peterson [aut, cre]
Maintainer: Ryan Andrew Peterson <ryan-peterson at uiowa.edu>
License: GPL-3
URL: https://github.com/petersonR/bestNormalize
NeedsCompilation: no
Citation: bestNormalize citation info
Materials: README NEWS
CRAN checks: bestNormalize results

Downloads:

Reference manual: bestNormalize.pdf
Vignettes: bestNormalize
Package source: bestNormalize_1.2.0.tar.gz
Windows binaries: r-devel: bestNormalize_1.2.0.zip, r-release: bestNormalize_1.2.0.zip, r-oldrel: bestNormalize_1.2.0.zip
OS X binaries: r-release: bestNormalize_1.2.0.tgz, r-oldrel: bestNormalize_1.2.0.tgz
Old sources: bestNormalize archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bestNormalize to link to this page.