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Causal Markov condition

The Markov condition (sometimes called Markov assumption) for a Bayesian network states that any node in a Bayesian network is conditionally… Expand
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Papers overview

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Highly Cited
2010
Highly Cited
2010
Inferring the causal structure that links n observables is usually based upon detecting statistical dependences and choosing… Expand
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2010
2010
The causal Markov condition (CMC) is a postulate that links observations to causality. It describes the conditional independences… Expand
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Highly Cited
2010
Highly Cited
2010
  • A. Dawid
  • NIPS Causality: Objectives and Assessment
  • 2010
  • Corpus ID: 11167064
Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them… Expand
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2007
2007
It is still a matter of controversy whether the Principle of the Common Cause (PCC) can be used as a basis for sound causal… Expand
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2006
2006
Using cross-country data, the authors evaluate historical determinants of protection of property rights. They examine four… Expand
2005
2005
  • D. Steel
  • The British Journal for the Philosophy of Science
  • 2005
  • Corpus ID: 18012144
The causal Markov condition (CMC) plays an important role in much recent work on the problem of causal inference from statistical… Expand
2004
2004
This paper explores the relationship between a manipulability conception of causation and the causal Markov condition (CM). We… Expand
Highly Cited
2002
Highly Cited
2002
  • N. Cartwright
  • The British Journal for the Philosophy of Science
  • 2002
  • Corpus ID: 121729213
In their rich and intricate paper ‘Independence, Invariance, and the Causal Markov Condition’, Daniel Hausman and James Woodward… Expand
Highly Cited
1999
Highly Cited
1999
This essay explains what the Causal Markov Condition says and defends the condition from the many criticisms that have been… Expand
1996
1996
This paper provides a priori cirteria for determing when a causal model is sufficiently complete to be considered a Bayesian… Expand
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