no_transform {bestNormalize} | R Documentation |
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 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, ...)
x |
A vector |
warn |
Should a warning result from infinite values? |
... |
additional arguments |
object |
an object of class 'no_transform' |
newdata |
a vector of data to be (potentially reverse) transformed |
inverse |
if TRUE, performs reverse transformation |
no_transform
creates a identity transformation object
that can be applied to new data via the predict
function.
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.
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)