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Cited by 545Bayesian Modeling and Causal InferenceStatistical Methods and InferenceGaussian Processes and Bayesian Inference

Ancestral graph Markov models

Richardson, Thomas, Spirtes, Peter·2002·The Annals of Statistics
DOI 10.1214/aos/1031689015
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Abstract

This paper introduces a class of graphical independence models that is closed under marginalization and conditioning but that contains all DAG independence models. This class of graphs, called maximal ancestral graphs, has two attractive features: there is at most one edge between each pair of vertices; every missing edge corresponds to an independence relation. These features lead to a simple parameterization of the corresponding set of distributions in the Gaussian case.

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Crossref · 10.1214/aos/1031689015

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  • The Markov equivalence class of a MAG can be represented uniquely by a partial ancestral graph (PAG).

    “Again, there is an identifiability problem here, as we can generally only identify the Markov equivalence class of the underlying MAG, which can be represented uniquely by a partial ancestral graph (PAG) [Richardson and Spirtes (2002), Ali, Richardson and Spirtes (2009)].”

    From A generalized back-door criterion (2015) · cites this paper as Richardson and Spirtes (2002)

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Authors
Richardson, T., & Spirtes, P.
Affiliations
  • University of Washington (US)
  • Florida Institute for Human and Machine Cognition (US)
ORCID
Venue
The Annals of Statistics
Publisher
Institute of Mathematical Statistics
Published
2002-08-01
Volume
30
Issue
4
Pages
962-1030
ISSN
  • 0090-5364 (ISSN-L)
  • 2168-8966
DOI
10.1214/aos/1031689015
OpenAlex
W2086331397
Cited by
545
References
0
Citations by year
2026: 20 · 2025: 19 · 2024: 26 · 2023: 26 · 2022: 23 · 2021: 30 · 2020: 39 · 2019: 29 · 2018: 29 · 2017: 30 · 2016: 23 · 2015: 28 · 2014: 31 · 2013: 28 · 2012: 41
FWCI
6.23
Type
journal article
Language
en
Open access
closed
Locations
  • The Annals of Statistics (publishedVersion)
  • Defense Technical Information Center (DTIC) (submittedVersion)
  • Project Euclid (Cornell University) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
  • Physical Sciences › Computer Science › Artificial Intelligence › Gaussian Processes and Bayesian Inference
Keywords
Markov model, missing edges, normal distribution

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