CCI: An R package for computational conditional Independence testing
Thorjussen, Christian; Liland, Kristian Hovde; Solberg, Lars Erik; Måge, Ingrid
Sammendrag
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.
Les publikasjonen her:
DOI
:
doi.org/10.1016/j.softx.2026.1...
NVA
:
hdl.handle.net/11250/5531112
Publikasjonsdetaljer
Tidsskrift : SoftwareX , 2026 , vol. 34 , pp. 1–8
Publikasjonstype : Vitenskapelig artikkel
