ML Anthology

Asymmetric Separation for Local Independence Graphs

Vanessa Didelez
UAI 2006
/uai/2006/didelez2006uai-asymmetric/

Abstract

Directed possibly cyclic graphs have been proposed by Didelez (2000) and Nodelmann et al. (2002) in order to represent the dynamic dependencies among stochastic processes. These dependencies are based on a generalization of Granger-causality to continuous time, first developed by Schweder (1970) for Markov processes, who called them local dependencies. They deserve special attention as they are asymmetric. In this paper we focus on their graphical representation and develop an asymmetric notion of separation. The properties of this graph separation as well as local independence are investigated in detail within a framework of asymmetric (semi)graphoids allowing insight into what information can be read off these graphs.

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Cite

Text

Didelez. "Asymmetric Separation for Local Independence Graphs." Conference on Uncertainty in Artificial Intelligence, 2006.

Markdown

[Didelez. "Asymmetric Separation for Local Independence Graphs." Conference on Uncertainty in Artificial Intelligence, 2006.](https://mlanthology.org/uai/2006/didelez2006uai-asymmetric/)

BibTeX

@inproceedings{didelez2006uai-asymmetric,
  title     = {{Asymmetric Separation for Local Independence Graphs}},
  author    = {Didelez, Vanessa},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {2006},
  url       = {https://mlanthology.org/uai/2006/didelez2006uai-asymmetric/}
}