Algorithms for quantifying associations, independence testing and causal inference from data.

(Conditional) Independence testing & Markov blanket feature selection using k-NN mutual information and conditional mutual information estimators. Supports continuous, discrete, and mixed data, as well as multiprocessing.

Python package for (conditional) independence testing and statistical functions related to causality.

MMD/HSIC-DUAL package implementing the MMD-DUAL and HSIC-DUAL test proposed in Learning Diverse Kernels for Aggregated Two-sample and Independence Testing by Zhou, Tian, Peng, Lei, Schrab, Sutherland and Liu: https://arxiv.org/abs/2510.11140

analysis of contingency tables and their residuals, with a bootstrap correction for multiple testing