Markov Properties of Nonrecursive Causal Models

@inproceedings{KOSTER1996MarkovPO,
  title={Markov Properties of Nonrecursive Causal Models},
  author={BY J. T. A. KOSTER},
  year={1996}
}
  • BY J. T. A. KOSTER
  • Published 1996
This paper aims to solve an often noted incompatibility between graphical chain models which elucidate the conditional independence structure of a set of random variables and simultaneous equations systems which focus on direct linear interactions and correlations between random variables. Various authors have argued that the incompatibility Ž arises mainly from the fact that in a simultaneous equations system e.g., . a LISREL model reciprocal causality is possible whereas this is not so in the… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-8 of 8 references

Marginalization and collapsibility in graphical interaction models

  • M. FRYDENBERG
  • Ann. Statist
  • 1990
Highly Influential
15 Excerpts

The chain graph Markov property

  • M. FRYDENBERG
  • Scand. J. Statist
  • 1990
Highly Influential
15 Excerpts

Properties of cyclic graphical models

  • T. RICHARDSON
  • MS thesis,
  • 1994
1 Excerpt

Linear recursive equations, covariance selection, and path analysis

  • N. WERMUTH
  • J. Amer. Statist. Assoc
  • 1980
1 Excerpt

The method of path coefficients

  • S. WRIGHT
  • Ann. Math. Statist
  • 1934
1 Excerpt

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