Identity transformation and center/scale transform — no

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.

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

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

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

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

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

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

# S3 method for 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

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.

Details

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

Examples

x <- rgamma(100, 1, 1)

no_transform_obj <- no_transform(x)
no_transform_obj
#> I(x) Transformation with 100 nonmissing obs.
p <- predict(no_transform_obj)
x2 <- predict(no_transform_obj, newdata = p, inverse = TRUE)

all.equal(x2, x)
#> [1] TRUE