A partial correlation-based algorithm for causal structure discovery with continuous variables

Authors:
Jean-Philippe Pellet;André Elisseeff
Affiliations:
IBM Research, Business Optimization Group, Rüschlikon, Switzerland and Swiss Federal Institute of Technology Zurich, Machine Learning Group, Institute of Computational Science, Zurich, Switze ...;IBM Research, Business Optimization Group, Rüschlikon, Switzerland
Venue:
IDA'07 Proceedings of the 7th international conference on Intelligent data analysis
Year:
2007

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Abstract

We present an algorithm for causal structure discovery suited in the presence of continuous variables. We test a version based on partial correlation that is able to recover the structure of a recursive linear equations model and compare it to the well-known PC algorithm on large networks. PC is generally outperformed in run time and number of structural errors.