exp_x | R Documentation |
Perform a exp(x) transformation
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, ...)
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 |
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.
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.
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)
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