Directed Cyclic Graphical Representations of Feedback Models

Abstract

The use of directed acyclic graphs (DAGs) to represent conditional independence relations among random variables has proved fruitful in a variety of ways. Recursive structural equation models are one kind of DAG model. However, non-recursive structural equation models of the kinds used to model economic processes are naturally represented by directeed cyclic graphs (DCG). For linear systems associated with DCGs with independent errors, a characterisation of conditional independence constraints is obtained, and it is shown that the result generalizes in a natural way to systems in which the error variables or noises are statistically dependent. For non-linear systems with independent errors a sufficient condition for conditional independence of variables in associated distributions is obtained.

Cite

Text

Spirtes. "Directed Cyclic Graphical Representations of Feedback Models." Conference on Uncertainty in Artificial Intelligence, 1995.

Markdown

[Spirtes. "Directed Cyclic Graphical Representations of Feedback Models." Conference on Uncertainty in Artificial Intelligence, 1995.](https://mlanthology.org/uai/1995/spirtes1995uai-directed/)

BibTeX

@inproceedings{spirtes1995uai-directed,
  title     = {{Directed Cyclic Graphical Representations of Feedback Models}},
  author    = {Spirtes, Peter},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {1995},
  pages     = {491-498},
  url       = {https://mlanthology.org/uai/1995/spirtes1995uai-directed/}
}