RCPC: A Sound Causal Discovery Algorithm under Orientation Unfaithfulness

Kenneth Lee, Murat Kocaoglu

Keywords: causal discovery, faithfulness

TL;DR: We show that an existing constraint-based discovery algorithm known as CPC is not complete and propose two orientation rules under adjacency faithfulness.

Abstract: In causal discovery, the constraint-based approaches often rely on an assumption known as faithfulness/stability, only the variables that are d-separated in a directed acyclic graph will be statistically independent. This assumption can be partitioned into two subconditions: orientation faithfulness and adjacency faithfulness. Under adjacency faithfulness, a sound algorithm known as CPC, a conservative version of PC algorithm, has been developed and is conjectured to be complete. In this work, we show that the CPC algorithm is not complete and propose two new sound orientation rules as part of a sound causal discovery algorithm called revised CPC (RCPC) under orientation unfaithfulness.

Submission Number: 11