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A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables
This video was recorded at 7th International Symposium on Intelligent Data Analysis, Ljubljana 2007. 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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