AI RESEARCH
How PC-based Methods Err: Towards Better Reporting of Assumption Violations and Small Sample Errors
arXiv CS.LG
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ArXi:2502.14719v2 Announce Type: replace-cross Causal discovery methods based on the PC algorithm are proven to be sound if all structural assumptions are fulfilled and all conditional independence tests are correct. This idealized setting is rarely given in real data. In this work, we first analyze how local errors can propagate throughout the output graph of a PC-based method, highlighting how consequential seemingly innocuous errors can become. Next, we