yeojohnson {bestNormalize} R Documentation

## Yeo-Johnson Normalization

### Description

Perform a Yeo-Johnson Transformation and center/scale a vector to attempt normalization

### Usage

yeojohnson(x, eps = 0.001, standardize = TRUE, ...)

## S3 method for class 'yeojohnson'
predict(object, newdata = NULL, inverse = FALSE, ...)

## S3 method for class 'yeojohnson'
print(x, ...)


### Arguments

 x A vector to normalize with Yeo-Johnson eps A value to compare lambda against to see if it is equal to zero standardize If TRUE, the transformed values are also centered and scaled, such that the transformation attempts a standard normal ... Additional arguments that can be passed to the estimation of the lambda parameter (lower, upper) object an object of class 'yeojohnson' newdata a vector of data to be (reverse) transformed inverse if TRUE, performs reverse transformation

### Details

yeojohnson estimates the optimal value of lambda for the Yeo-Johnson transformation. This transformation can be performed on new data, and inverted, via the predict function.

The Yeo-Johnson is similar to the Box-Cox method, however it allows for the transformation of nonpositive data as well. The step_YeoJohnson function in the recipes package is another useful resource (see references).

### Value

A list of class yeojohnson with elements

 x.t transformed original data x original data mean mean after transformation but prior to standardization sd sd after transformation but prior to standardization lambda estimated lambda value for skew transformation n number of nonmissing observations norm_stat Pearson's P / degrees of freedom standardize Was the transformation standardized

The predict function returns the numeric value of the transformation performed on new data, and allows for the inverse transformation as well.

### References

Yeo, I. K., & Johnson, R. A. (2000). A new family of power transformations to improve normality or symmetry. Biometrika.

Max Kuhn and Hadley Wickham (2017). recipes: Preprocessing Tools to Create Design Matrices. R package version 0.1.0.9000. https://github.com/topepo/recipes

### Examples


x <- rgamma(100, 1, 1)

yeojohnson_obj <- yeojohnson(x)
yeojohnson_obj
p <- predict(yeojohnson_obj)
x2 <- predict(yeojohnson_obj, newdata = p, inverse = TRUE)

all.equal(x2, x)



[Package bestNormalize version 1.9.1 Index]