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bestNormalize  

Normalizing Transformation Functions
View on CRAN: Click here


Download and install bestNormalize package within the R console
Install from CRAN:
install.packages("bestNormalize")

Install from Github:
library("remotes")
install_github("cran/bestNormalize")

Install by package version:
library("remotes")
install_version("bestNormalize", "1.9.2")



Attach the package and use:
library("bestNormalize")
Maintained by
Ryan Andrew Peterson
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-11-14
Latest Update: 2023-08-18
Description:
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. It estimates the normalization efficacy of other commonly used transformations, and it allows users to specify custom transformations or normalization statistics. Finally, functionality can be integrated into a machine learning workflow via recipes.
How to cite:
Ryan Andrew Peterson (2017). bestNormalize: Normalizing Transformation Functions. R package version 1.9.2, https://cran.r-project.org/web/packages/bestNormalize. Accessed 10 Mar. 2026.
Previous versions and publish date:
0.2.2 (2017-11-14 17:26), 1.0.0 (2018-01-04 21:42), 1.0.1 (2018-02-05 19:48), 1.1.0 (2018-05-29 22:50), 1.2.0 (2018-05-31 00:28), 1.3.0 (2018-09-25 19:40), 1.4.0 (2019-05-13 21:00), 1.4.2 (2019-08-20 23:20), 1.4.3 (2020-01-27 18:00), 1.5.0 (2020-04-18 06:20), 1.6.0 (2020-05-20 23:40), 1.6.1 (2020-06-08 21:40), 1.7.0 (2021-03-02 00:10), 1.8.0 (2021-06-03 13:20), 1.8.1 (2021-09-02 16:50), 1.8.2 (2021-09-16 07:10), 1.8.3 (2022-06-13 22:50), 1.9.0 (2023-03-15 22:20), 1.9.1 (2023-08-18 10:42)
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