The Box-Cox (method = “BoxCox”), are being used to transform the predictor variables.
The Box-Cox transformation was developed for transforming the response variable while another method,
However, the Box-Cox method is simpler, more computationally efficient and is equally effective for estimating power transformations.
The Yeo-Johnson transformation is similar to the Box-Cox model but can accommodate predictors with zero and/or negative values
(while the predictors values for the Box-Cox transformation must be strictly positive.)
method = “center” subtracts the mean of the predictor’s data (again from the data in x)
from the predictor values while.
method = “scale” divides by the standard deviation.