A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables

author: Jean-Philippe Pellet, IBM Zurich Research Lab
published: Oct. 8, 2007,   recorded: September 2007,   views: 4358


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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.

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