exp_x: exp(x) Transformation

In petersonR/bestNormalize: Normalizing Transformation Functions

exp(x) Transformation

Description

Perform a exp(x) transformation

Usage

exp_x(x, standardize = TRUE, warn = TRUE, ...)

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

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

Arguments

x	A vector to normalize with with x
standardize	If TRUE, the transformed values are also centered and scaled, such that the transformation attempts a standard normal
warn	Should a warning result from infinite values?
...	additional arguments
object	an object of class 'exp_x'
newdata	a vector of data to be (potentially reverse) transformed
inverse	if TRUE, performs reverse transformation

Details

exp_x performs a simple exponential transformation in the context of bestNormalize, such that it creates a transformation that can be estimated and applied to new data via the predict function.

Value

A list of class exp_x 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
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.

Examples

x <- rgamma(100, 1, 1)

exp_x_obj <- exp_x(x)
exp_x_obj
p <- predict(exp_x_obj)
x2 <- predict(exp_x_obj, newdata = p, inverse = TRUE)

all.equal(x2, x)

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