RobPy: a Python Package for Robust Statistical Methods

Understand

Robust estimation provides essential tools for analyzing data that contain outliers, ensuring that statistical models remain reliable even in the presence of some anomalous data.

• While robust methods have long been available in R, users of Python have lacked a comprehensive package that offers these methods in a cohesive framework.
• RobPy addresses this gap by offering a wide range of robust methods in Python, built upon established libraries including NumPy, SciPy, and scikit-learn.
• This package includes tools for robust preprocessing, univariate estimation, covariance matrices, regression, and principal component analysis, which are able to detect outliers and to mitigate their effect.