BoxCoxYeoJohnson
BoxCoxYeoJohnson is a family of power transformations used in statistics to stabilize variance and make data more normally distributed. It is designed to handle data that include positive, zero, and negative values by combining features of the Box-Cox transformation and the Yeo-Johnson transformation. The goal is to provide a single, monotonic transformation that can be applied across the entire real line, improving the suitability of data for parametric modeling.
Conceptually, BoxCoxYeoJohnson extends the Box-Cox approach, which requires strictly positive observations, by incorporating the Yeo-Johnson framework,
Estimation and use: the transformation parameter is typically estimated by maximizing likelihood under the assumption of
See also: Box-Cox transformation; Yeo-Johnson transformation; data normalization in statistical modeling.