A Criterion for Parameter Identification in Structural Equation Models

2012/06/20 by Jin Tian, Tian, Jin
Computer Science · Decision Sciences · Mathematics · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Methodology (stat.ME) #Multi-Criteria Decision Making #cs.AI #stat.ME

paper · pdf · doi:10.48550/arxiv.1206.5289

Appears in Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (UAI2007)

arxiv created 2012/06/20 · openalex publication_date 2012/06/20 · arxiv updated 2012/06/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper deals with the problem of identifying direct causal effects in recursive linear structural equation models. The paper establishes a sufficient criterion for identifying individual causal effects and provides a procedure computing identified causal effects in terms of observed covariance matrix.

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