boxcox: Box-Cox Normalization

In petersonR/bestNormalize: Normalizing Transformation Functions

Box-Cox Normalization

Description

Perform a Box-Cox transformation and center/scale a vector to attempt normalization

Usage

boxcox(x, standardize = TRUE, ...)

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

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

Arguments

x	A vector to normalize with Box-Cox
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, epsilon)
object	an object of class 'boxcox'
newdata	a vector of data to be (reverse) transformed
inverse	if TRUE, performs reverse transformation

Details

boxcox estimates the optimal value of lambda for the Box-Cox transformation. This transformation can be performed on new data, and inverted, via the predict function.

The function will return an error if a user attempt to transform nonpositive data.

Value

A list of class boxcox 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

Box, G. E. P. and Cox, D. R. (1964) An analysis of transformations. Journal of the Royal Statistical Society B, 26, 211-252.

See Also

boxcox

Examples

x <- rgamma(100, 1, 1)

bc_obj <- boxcox(x)
bc_obj
p <- predict(bc_obj)
x2 <- predict(bc_obj, newdata = p, inverse = TRUE)

all.equal(x2, x)

petersonR/bestNormalize documentation built on March 15, 2024, 9:29 a.m.