CCI: An R package for computational conditional Independence testing

The CCI package provides a computational framework for conditional independence testing in R, combining machine learning models with Monte Carlo cross-validation to deliver robust error control across complex data structures. CCI is model-agnostic, user-friendly, and supports continuous, categorical, and mixed data. Key functionalities include automated hyperparameter tuning, flexible direction selection, and visualization tools for null distributions and p-values. By lowering the barrier to rigorous conditional independence testing, the package facilitates advances in causal inference research and applied data analysis.