Relational Causal Model and Tools
This library provides an up-to-date implementation of Relational Causal Model [1,2,3,4], which provides classes for presenting relational schema, skeleton, and ground graphs.
RpCD, a sound and (only) complete structure learning algorithm  is developed with theoretical evaluation in mind.
To learn a causal structure from real data, please check out a separate library
RRCD, robust relational causal discovery , which is dependent on this library developed by the same author.
 Marc Maier, Brian Taylor, Huseyin Oktay, and David Jensen (2010). AAAI. Learning Causal Models of Relational Domains.
 Marc Maier, Katerina Marazopoulou, David Arbour, and David Jensen (2013). UAI. A Sound and Complete Algorithm for Learning Causal Models from Relational Data
 Sanghack Lee and Vasant Honavar (2016). AAAI. On Learning Causal Models from Relational Data
 Sanghack Lee and Vasant Honavar (2016). UAI. A Characterization of Markov Equivalence Classes for Relational Causal Model with Path Semantics.
 Sanghack Lee and Vasant Honavar (2019). UAI. Towards Robust Relational Causal Discovery.