Learning LWF Chain Graphs: an Order Independent Algorithm

• URL: http://arxiv.org/abs/2005.14037v1
• Date: Wed, 27 May 2020 01:05:49 GMT
• Title: Learning LWF Chain Graphs: an Order Independent Algorithm
• Authors: Mohammad Ali Javidian, Marco Valtorta and Pooyan Jamshidi
• Abstract summary: We present a PC-like algorithm that finds the structure of chain graphs under the faithfulness assumption. We prove that our PC-like algorithm is order dependent, in the sense that the output can depend on the order in which the variables are given. We propose two modifications of the PC-like algorithm that remove part or all of this order dependence.
• Score: 2.3333090554192615
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: LWF chain graphs combine directed acyclic graphs and undirected graphs. We present a PC-like algorithm that finds the structure of chain graphs under the faithfulness assumption to resolve the problem of scalability of the proposed algorithm by Studeny (1997). We prove that our PC-like algorithm is order dependent, in the sense that the output can depend on the order in which the variables are given. This order dependence can be very pronounced in high-dimensional settings. We propose two modifications of the PC-like algorithm that remove part or all of this order dependence. Simulation results under a variety of settings demonstrate the competitive performance of the PC-like algorithms in comparison with the decomposition-based method, called LCD algorithm, proposed by Ma et al. (2008) in low-dimensional settings and improved performance in high-dimensional settings.

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