Power Transform Revisited: Numerically Stable, and Federated

ArXi:2510.04995v3 Announce Type: replace Power transforms are popular parametric methods for making data Gaussian-like, and are widely used as preprocessing steps in statistical analysis and machine learning. However, we find that direct implementations of power transforms suffer from severe numerical instabilities, which can lead to incorrect results or even crashes. In this paper, we provide a comprehensive analysis of the sources of these instabilities and propose effective remedies.