exp_x {bestNormalize} R Documentation

## 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)

```

[Package bestNormalize version 1.8.0 Index]