Work

A Characterization of Interventional Distributions in Semi-Markovian Causal Models

Year: 2006

Type: article

Abstract: We offer a complete characterization of the set of distributions that could be induced by local interventions on variables governed by a causal Bayesian network of unknown structure, in which some of the variables remain unmeasured. We show that such distributions are constrained by a simply formulated set of inequalities, from which bounds can be derived on causal effects that are not directly measured in randomized experiments.

Source: eScholarship (California Digital Library)

Authors: Jin Tian, Changsung Kang, Judea Pearl

Institutions: Iowa State University, University of California, Los Angeles

Language: English

Topic: Bayesian Modeling and Causal Inference

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, Multidisciplinary University Research Initiative, Office of Naval Research, Air Force Office of Scientific Research

Award: CAREER: Reasoning with Cause and Effect: Model Testing, Axiomatization, and Identification

OpenAlex ID: W1483120523

FWCI: 0.354

Cites: 12

Cited by: 6

Related to: 10