Identification of Strong Edges in AMP Chain Graphs

Jose M. Peña
Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence, PMLR R16:32-41, 2018.

Abstract

The essential graph is a distinguished member of a Markov equivalence class of AMP chain graphs. However, the directed edges in the es- sential graph are not necessarily strong or in- variant, i.e. they may not be shared by every member of the equivalence class. Likewise for the undirected edges. In this paper, we develop a procedure for identifying which edges in an essential graph are strong. We also show how this makes it possible to bound some causal ef- fects when the true chain graph is unknown.

Cite this Paper

BibTeX
@InProceedings{pmlr-vR16-pena18a, title = {Identification of Strong Edges in {AMP} Chain Graphs}, author = {Pe{\~n}a, Jose M.}, booktitle = {Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence}, pages = {32--41}, year = {2018}, editor = {Globerson, Amir and Silva, Ricardo}, volume = {R16}, series = {Proceedings of Machine Learning Research}, month = {06--10 Aug}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/r16/main/assets/pena18a/pena18a.pdf}, url = {https://proceedings.mlr.press/r16/pena18a.html}, abstract = {The essential graph is a distinguished member of a Markov equivalence class of AMP chain graphs. However, the directed edges in the es- sential graph are not necessarily strong or in- variant, i.e. they may not be shared by every member of the equivalence class. Likewise for the undirected edges. In this paper, we develop a procedure for identifying which edges in an essential graph are strong. We also show how this makes it possible to bound some causal ef- fects when the true chain graph is unknown.}, note = {Reissued by PMLR on 04 October 2026.} }
Endnote
%0 Conference Paper %T Identification of Strong Edges in AMP Chain Graphs %A Jose M. Peña %B Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence %C Proceedings of Machine Learning Research %D 2018 %E Amir Globerson %E Ricardo Silva %F pmlr-vR16-pena18a %I PMLR %P 32--41 %U https://proceedings.mlr.press/r16/pena18a.html %V R16 %X The essential graph is a distinguished member of a Markov equivalence class of AMP chain graphs. However, the directed edges in the es- sential graph are not necessarily strong or in- variant, i.e. they may not be shared by every member of the equivalence class. Likewise for the undirected edges. In this paper, we develop a procedure for identifying which edges in an essential graph are strong. We also show how this makes it possible to bound some causal ef- fects when the true chain graph is unknown. %Z Reissued by PMLR on 04 October 2026.
APA
Peña, J.M.. (2018). Identification of Strong Edges in AMP Chain Graphs. Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence, in Proceedings of Machine Learning Research R16:32-41 Available from https://proceedings.mlr.press/r16/pena18a.html. Reissued by PMLR on 04 October 2026.

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