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bestNormalize
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
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[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 09 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)
Other packages that cited bestNormalize R package
View bestNormalize citation profile
Other R packages that bestNormalize depends,
imports, suggests or enhances
Complete documentation for bestNormalize
Functions, R codes and Examples using
the bestNormalize R package
Some associated functions: arcsinh_x . autotrader . bestLogConstant . bestNormalize-package . bestNormalize . binarize . boxcox . double_reverse_log . exp_x . lambert . log_x . no_transform . orderNorm . plot.bestNormalize . reexports . sqrt_x . step_best_normalize . step_orderNorm . yeojohnson .
Some associated R codes: arcsinh_x.R . bestLogConstant.R . bestNormalize-package.R . bestNormalize.R . binarize.R . boxcox.R . data.R . double_reverse_log.R . exp_x.R . lambert.R . log_x.R . no_transform.R . orderNorm.R . plots.R . sqrt_x.R . step_best_normalize.R . step_orderNorm.R . yeojohnson.R . Full bestNormalize package functions and examples
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