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Activity Number: 518 - Modern Graphical Modeling of Complex Biomedical Systems
Type: Invited
Date/Time: Thursday, August 6, 2020 : 1:00 PM to 2:50 PM
Sponsor: ENAR
Abstract #308095
Title: Edge-Selection Priors for Graphs Estimation with Applications to Complex Data
Author(s): Marina Vannucci*
Companies: Rice University
Keywords: Bayesian statistics; Graphical models; Spike-and-slab priors

There is now a huge literature on Bayesian methods for variable selection in linear models that use spike-and-slab priors. Such methods, in particular, have been quite successful for applications in a variety of different fields. A parallel methodological development has happened in graphical models, where priors are specified on precision matrices. In this talk I will describe priors for edge selection for the estimation of multiple graphs that may share common features, such as presence/absence of edges or strengths of connections. I will motivate the development of the models using specific applications from neuroimaging and from studies that use large-scale genomic data. If time allows I will also describe extensions of the models to non-Gaussian data and computational challenges.

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

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