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Activity Number: 355 - Advanced Bayesian Topics (Part 4)
Type: Contributed
Date/Time: Thursday, August 12, 2021 : 10:00 AM to 11:50 AM
Sponsor: Section on Bayesian Statistical Science
Abstract #319063
Title: Gaussian Bayesian Network Comparisons with Graph Ordering Unknown
Author(s): Hongmei Zhang* and Xianzheng Huang and Shengtong Han and Faisal Rezwan and Wilfried Karmaus and Hasan Arshad and John Holloway
Companies: University of Memphis and University of South Carolina and University of Wisconsin, Milwaukee and Cranfield University and University of Memphis and University of Southampton and University of Southampton
Keywords: Bayesian methods; DNA methylation; Single queue equi-energy; Variable selection; Ordering

A Bayesian approach is proposed that unifies Gaussian Bayesian network constructions and comparisons between two networks (identical or differential) for data with graph ordering unknown. When sampling graph ordering, to escape from local maximums, an adjusted single queue equi-energy algorithm is applied. The conditional posterior probability mass function for network differentiation is derived and its asymptotic proposition is theoretically assessed. Simulations are used to demonstrate the approach and compare with existing methods. Based on epigenetic data at a set of DNA methylation sites (CpG sites), the proposed approach is further examined on its ability to detect network di erentiations. Findings from theoretical assessment, simulations, and real data applications support the ecacy and eciency of the proposed method for network comparisons.

Authors who are presenting talks have a * after their name.

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