no_transform {bestNormalize}

Identity transformation and center/scale transform

Description

Perform an identity transformation. Admittedly it seems odd to have a dedicated function to essentially do I(x), but it makes sense to keep the same syntax as the other transformations so it plays nicely with them. As a benefit, the bestNormalize function will also show a comparable normalization statistic for the untransformed data. If standardize == TRUE, center_scale passes to bestNormalize instead.

Usage

no_transform(x, warn = TRUE, ...)

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

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

center_scale(x, warn = TRUE, ...)

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

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

## S3 method for class 'no_transform'
tidy(x, ...)

Arguments

x

A 'no_transform' object.

warn

Should a warning result from infinite values?

...

not used

object

an object of class 'no_transform'

newdata

a vector of data to be (potentially reverse) transformed

inverse

if TRUE, performs reverse transformation

Details

no_transform creates a identity transformation object that can be applied to new data via the predict function.

Value

A list of class no_transform with elements

x.t

transformed original data

x

original data

n

number of nonmissing observations

norm_stat

Pearson's P / degrees of freedom

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)

no_transform_obj <- no_transform(x)
no_transform_obj
p <- predict(no_transform_obj)
x2 <- predict(no_transform_obj, newdata = p, inverse = TRUE)

all.equal(x2, x)