Discovering Probabilistic Causal Relationships: A Comparison Between Two Methods

  • Floriana Esposito
  • Donato Malerba
  • Giovanni Semeraro
Conference paper
Part of the Lecture Notes in Statistics book series (LNS, volume 89)


This paper presents a comparison between two different approaches to statistical causal inference, namely Glymour et al.’s approach based on constraints on correlations and Pearl and Verma’s approach based on conditional independencies. The methods differ both in the kind of constraints considered while selecting a causal model and in the way they search for the model which better fits the sample data. Some experiments show that they are complementary in several aspects.


Latent Variable Latent Structure Causal Model Conditional Independency Spurious Association 
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Copyright information

© Springer-Verlag New York, Inc. 1994

Authors and Affiliations

  • Floriana Esposito
    • 1
  • Donato Malerba
    • 1
  • Giovanni Semeraro
    • 1
  1. 1.Dipartimento di InformaticaUniversità degli Studi di BariBariItaly

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